Instruction:
Text: the rest of the volume presents the inscriptions , giving the circumstances of finding .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['component whole', 'NA', 'instrument agency', 'member collection', 'cause effect', 'entity destination', 'content container', 'message topic', 'product producer', 'entity origin']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "message topic", "head": "volume", "tail": "inscriptions"}]


Instruction:
Text: each question requires a text note to explain the rating .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['component whole', 'NA', 'instrument agency', 'member collection', 'cause effect', 'entity destination', 'content container', 'message topic', 'product producer', 'entity origin']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "message topic", "head": "note", "tail": "rating"}]


Instruction:
Text: this weekly economic publication analyzes and interprets financial , commercial and industrial developments .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['component whole', 'NA', 'instrument agency', 'member collection', 'cause effect', 'entity destination', 'content container', 'message topic', 'product producer', 'entity origin']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "message topic", "head": "publication", "tail": "developments"}]


Instruction:
Text: the exhibition examines the first sustained contacts between american people and european explorers , conquerors and settlers from 1492 to 1600 .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['component whole', 'NA', 'instrument agency', 'member collection', 'cause effect', 'entity destination', 'content container', 'message topic', 'product producer', 'entity origin']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "message topic", "head": "exhibition", "tail": "contacts"}]


Instruction:
Text: the petition described the oil as being useful for salads and culinary purposes .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['component whole', 'NA', 'instrument agency', 'member collection', 'cause effect', 'entity destination', 'content container', 'message topic', 'product producer', 'entity origin']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "message topic", "head": "petition", "tail": "oil"}]


Instruction:
Text: most of his speeches at the rallies have been about the economy and the need to fight against corruption .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['component whole', 'NA', 'instrument agency', 'member collection', 'cause effect', 'entity destination', 'content container', 'message topic', 'product producer', 'entity origin']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "message topic", "head": "speeches", "tail": "economy"}]


Instruction:
Text: one year later , a follow-up workshop was held to provide a focused discussion on these issues from a research , practice and policy perspective .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['component whole', 'NA', 'instrument agency', 'member collection', 'cause effect', 'entity destination', 'content container', 'message topic', 'product producer', 'entity origin']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "message topic", "head": "discussion", "tail": "issues"}]


Instruction:
Text: the book asserts the intrinsic relationship between psychotherapy , human rights and politics .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['component whole', 'NA', 'instrument agency', 'member collection', 'cause effect', 'entity destination', 'content container', 'message topic', 'product producer', 'entity origin']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "message topic", "head": "book", "tail": "relationship"}]


Instruction:
Text: his 'intensely personal ' talk tackles the great challenges facing immigrants today .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['component whole', 'NA', 'instrument agency', 'member collection', 'cause effect', 'entity destination', 'content container', 'message topic', 'product producer', 'entity origin']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "message topic", "head": "talk", "tail": "challenges"}]


Instruction:
Text: the purpose of the class was to examine the therapeutic benefits of writing and to discern whether writing can be a help or a hinderance in some situations .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['component whole', 'NA', 'instrument agency', 'member collection', 'cause effect', 'entity destination', 'content container', 'message topic', 'product producer', 'entity origin']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "message topic", "head": "class", "tail": "therapeutic benefits"}]


Instruction:
Text: An art exhibit at the Hakawati Theatre in Arab east Jerusalem was a series of portraits of Palestinians killed in the rebellion .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Hakawati Theatre", "tail": "Jerusalem"}]


Instruction:
Text: PERUGIA , Italy ( AP )
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "PERUGIA", "tail": "Italy"}, {"relation": "Organization based in", "head": "AP", "tail": "PERUGIA"}, {"relation": "Organization based in", "head": "AP", "tail": "Italy"}]


Instruction:
Text: Reagan sounded positive notes reminiscent of earlier speeches throughout his political career _ the pre-eminent position of ` ` We the People ' ' in the American system , the image of America as a shining ` ` city upon a hill , ' ' the importance of paying more attention to American history .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Reagan", "tail": "America"}]


Instruction:
Text: There was no mention of the ` ` iron triangle ' ' of members of Congress , the news media and special interest groups who , in a speech to political appointees in Washington on Dec. 13 , Reagan claimed had prevented his administration from balancing the federal budget .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Congress", "tail": "Washington"}]


Instruction:
Text: Nor did he argue , as he did in a speech at the University of Virginia in Charlottesville Dec. 16 , that Congress had perpetuated a dangerous situation in Central America by its ` ` on-again , off-again indecisiveness ' ' on his program of aid to the anti-communist Contra rebels .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "University of Virginia", "tail": "Charlottesville"}]


Instruction:
Text: Wright , a University of Texas law professor , served as one of Nixon 's lawyers in 1973 and 1974 while the Watergate special prosecutor was trying to subpoena the White House tapes .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Wright", "tail": "University of Texas"}]


Instruction:
Text: An enraged Nikita Khrushchev instructed Soviet ships to ignore President Kennedy 's naval blockade during the Cuban missile crisis , but the order was reversed just hours before an inevitable confrontation , according to a new book .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Nikita Khrushchev", "tail": "Soviet"}]


Instruction:
Text: Anastas Mikoyan , then Soviet first deputy premier , was the catalyst for the reversal of Khrushchev 's order , according to the authors .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Anastas Mikoyan", "tail": "Soviet"}, {"relation": "Live in", "head": "Khrushchev", "tail": "Soviet"}]


Instruction:
Text: Mikoyan ` ` preempted Khrushchev 's order to run the blockade and ordered Soviet ships to stop just short of the quarantine line , ' ' they say .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Mikoyan", "tail": "Soviet"}, {"relation": "Live in", "head": "Khrushchev", "tail": "Soviet"}]


Instruction:
Text: But the authors suggested that Alekseev , along with others in the Soviet diplomatic corps , were not receiving accurate information from Moscow about the missiles .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Alekseev", "tail": "Soviet"}]


Instruction:
Text: MILAN , Italy ( AP )
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "MILAN", "tail": "Italy"}, {"relation": "Organization based in", "head": "AP", "tail": "MILAN"}, {"relation": "Organization based in", "head": "AP", "tail": "Italy"}]


Instruction:
Text: Hot Springs National Park , Ark. ;
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Hot Springs National Park", "tail": "Ark."}]


Instruction:
Text: Aguadilla , Puerto Rico ;
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Aguadilla", "tail": "Puerto Rico"}]


Instruction:
Text: Locations containing suitable federally owned land were listed as : Fort Wainwright annex , Fairbanks , Alaska ;
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Fort Wainwright annex", "tail": "Fairbanks"}, {"relation": "Located in", "head": "Fort Wainwright annex", "tail": "Alaska"}, {"relation": "Located in", "head": "Fairbanks", "tail": "Alaska"}]


Instruction:
Text: ATLANTIC CITY , N.J .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "ATLANTIC CITY", "tail": "N.J ."}]


Instruction:
Text: FRESNO , Calif .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "FRESNO", "tail": "Calif ."}]


Instruction:
Text: Dancers of Moscow 's Bolshoi Ballet in Moscow and Leningrad 's Kirov Ballet , together with opera singers from the Armenian capital of Yerevan , joined U.S. sopranos June Anderson and Carol Vaness and British dancers and singers .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Bolshoi Ballet", "tail": "Moscow"}, {"relation": "Organization based in", "head": "Bolshoi Ballet", "tail": "Moscow"}, {"relation": "Organization based in", "head": "Kirov Ballet", "tail": "Leningrad"}, {"relation": "Live in", "head": "June Anderson", "tail": "U.S."}, {"relation": "Live in", "head": "Carol Vaness", "tail": "U.S."}]


Instruction:
Text: Boston University 's Michael D. Papagiannis said he believes the crater was created 100 million years ago when a 50-mile-wide meteorite slammed into the Earth .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Michael D. Papagiannis", "tail": "Boston University"}]


Instruction:
Text: It is roughly bounded by Ostined , Lesny and Liberec in Czechoslovakia and Gmund in Austria .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Ostined", "tail": "Czechoslovakia"}, {"relation": "Located in", "head": "Lesny", "tail": "Czechoslovakia"}, {"relation": "Located in", "head": "Liberec", "tail": "Czechoslovakia"}, {"relation": "Located in", "head": "Gmund", "tail": "Austria"}]


Instruction:
Text: BONE , Idaho ( AP )
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "BONE", "tail": "Idaho"}]


Instruction:
Text: ` ` Temperatures didn 't get too low , but the wind chill was bad , ' ' said Bingham County Sheriff 's Lt. Bill Gordon .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Bill Gordon", "tail": "Bingham County"}]


Instruction:
Text: Canada 's ambassador , Yves Fortier , said the resolution contained ` ` a one-sided account. ' '
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Yves Fortier", "tail": "Canada"}]


Instruction:
Text: ` ` Either luck or good fortune was on my side , ' ' the shaken teacher , Donald Miller , said through United Federation of Teachers spokesman Bert Shanas .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Bert Shanas", "tail": "United Federation of Teachers"}]


Instruction:
Text: ` ` We 're quite proud to be flying the third flight since the ( Challenger ) accident , ' ' Navy Capt. Michael Coats said during the final preflight news conference Wednesday .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Michael Coats", "tail": "Navy"}]


Instruction:
Text: Gale-force winds were reported in California late Wednesday , where gusts reached 69 mph at Ontario and 57 mph at El Toro .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Ontario", "tail": "California"}, {"relation": "Located in", "head": "El Toro", "tail": "California"}]


Instruction:
Text: Temperatures around the nation at 2 a.m. EST ranged from 9 degrees below zero at Yellowstone , Wyo. , to 85 degrees at McAllen , Texas .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Yellowstone", "tail": "Wyo."}, {"relation": "Located in", "head": "McAllen", "tail": "Texas"}]


Instruction:
Text: ` ` We see nothing right now that would make any difference , ' ' said Steve Wright , who directs DOE environmental studies at the SRP .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Steve Wright", "tail": "DOE"}]


Instruction:
Text: The eight-pound bomb had a detonator charge , similar to a shotgun shell , that emits smoke when it hits the ground , said Bert Byers , spokesman for Cecil Field Naval Air Station .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Bert Byers", "tail": "Cecil Field Naval Air Station"}]


Instruction:
Text: Urutigoechea and the others were arrested Wednesday in the cities of Bayonee and Bonloc in southwestern France in Poitiers in west-central France .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Bayonee", "tail": "France"}, {"relation": "Located in", "head": "Bayonee", "tail": "France"}, {"relation": "Located in", "head": "Bonloc", "tail": "France"}, {"relation": "Located in", "head": "Bonloc", "tail": "France"}, {"relation": "Located in", "head": "Poitiers", "tail": "France"}, {"relation": "Located in", "head": "Poitiers", "tail": "France"}]


Instruction:
Text: Judith C. Toth says she returned for a fourth term in Maryland 's House of Delegates because she couldn 't find a better job .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "House of Delegates", "tail": "Maryland"}]


Instruction:
Text: ` ` We forwarded blood samples from the coyotes to the Center for Disease Control in Fort Collins and on Jan. 3 they confirmed the presence of plague. ' '
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Center for Disease Control", "tail": "Fort Collins"}]


Instruction:
Text: Hatcher also fled to the Onondaga territory but has since moved to a Shoshone-Bannock reservation in Idaho .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Shoshone-Bannock reservation", "tail": "Idaho"}]


Instruction:
Text: Albert O. Harjula , 29 , of Thomaston , became trapped first , said Paul Fournier , a spokesman for the state Department of Inland Fisheries and Wildlife .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Albert O. Harjula", "tail": "Thomaston"}, {"relation": "Work for", "head": "Paul Fournier", "tail": "Department of Inland Fisheries and Wildlife"}]


Instruction:
Text: To meet tritium needs , the report repeated previous administration recommendations for the construction of a $3.2 billion heavy water reactor at Savannah River and a $3.6 billion new design gas-cooled reactor at the Energy Department facility at Idaho Falls , Idaho .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Idaho Falls", "tail": "Idaho"}]


Instruction:
Text: An architect of President Nixon 's unsuccessful executive-privilege Watergate defense is a top prospect for the post of U.S. solicitor in the new Bush administration .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Bush", "tail": "U.S."}]


Instruction:
Text: Also under consideration are two conservative federal appellate judges appointed by President Reagan : Ralph K. Winter of the 2nd U.S. Circuit Court of Appeals in New York and Kenneth Starr of the U.S. Circuit Court of Appeals for the District of Columbia .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Ralph K. Winter", "tail": "2nd U.S. Circuit Court of Appeals"}, {"relation": "Organization based in", "head": "2nd U.S. Circuit Court of Appeals", "tail": "New York"}, {"relation": "Work for", "head": "Kenneth Starr", "tail": "U.S. Circuit Court of Appeals"}, {"relation": "Organization based in", "head": "U.S. Circuit Court of Appeals", "tail": "District of Columbia"}]


Instruction:
Text: Reagan recalled that on the 40th anniversary of the Normandy landings he read a letter from a young woman whose late father had fought at Omaha Beach , a Normandy sector .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Omaha Beach", "tail": "Normandy"}]


Instruction:
Text: After buying the shawl for $1 , 600 , Darryl Breniser of Blue Ball , said the approximately 2-by-5 foot shawl was worth the money .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Darryl Breniser", "tail": "Blue Ball"}]


Instruction:
Text: Terry Hands , the subsidized theater 's artistic director , unveiled a new ` ` one-year , two-season work cycle ' ' under which actors will commit themselves to one 60-week contract , playing the first half of the season at the company 's home theater in Stratford-upon-Avon before transferring the productions to its London base at the Barbican .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Barbican", "tail": "London"}]


Instruction:
Text: NASHVILLE , Tenn .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "NASHVILLE", "tail": "Tenn ."}]


Instruction:
Text: TUNIS , Tunisia ( AP )
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "TUNIS", "tail": "Tunisia"}]


Instruction:
Text: Gadhafi requested the meeting of foreign ministers after two U.S. Navy planes downed the Libyan jets , which American officials say were about to attack the U.S. craft .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Navy", "tail": "U.S."}, {"relation": "Organization based in", "head": "Navy", "tail": "U.S."}]


Instruction:
Text: ` ` The U.S. has the biggest stock of chemical arms in the world , and it is trying to obstruct other countries from having their own , ' ' said Arab League Secretary-General Chedli Klibi .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Chedli Klibi", "tail": "Arab League"}]


Instruction:
Text: ` ` These are the tactics of a marginalized force driven to extremes by desperation , ' ' said Abrams , whose 3 -LCB- -year service as head of the Latin America bureau will end next week with the inauguration of President-elect Bush .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Abrams", "tail": "Latin America bureau"}]


Instruction:
Text: King was killed April 4 , 1968 , in Memphis , Tenn. , and what would be his 60th birthday Sunday is celebrated as a national holiday Monday ; the celebration began with several events on Thursday .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Memphis", "tail": "Tenn."}]


Instruction:
Text: Soviet Foreign Eduard A. Shevardnadze is to visit China next month to pave the way for the first Chinese-Soviet summit in 30 years , Chinese television reported Monday .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Eduard A. Shevardnadze", "tail": "Soviet"}]


Instruction:
Text: In Beijing Thursday , spokesman Li repeated China 's position that the key to the solution of the Cambodian conflict ` ` lies in the genuine and complete Vietnamese troop withdrawal at the earliest possible date and effective international supervision. ' '
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Li", "tail": "Beijing"}, {"relation": "Live in", "head": "Li", "tail": "China"}]


Instruction:
Text: During that time , an estimated 2 million of Cambodia 's 8 million people died from Khmer Rouge executions , famine and civil unrest .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Khmer Rouge", "tail": "Cambodia"}]


Instruction:
Text: Walesa , a shipyard electrician who founded the independent Solidarity union movement in 1980 , said Poles are restive and fed up with high prices and shortages .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Walesa", "tail": "Solidarity"}]


Instruction:
Text: The plane , owned by Bradley First Air , of Ottawa , Canada , was carrying cargo to Montreal for Emery Air Freight Corp. , an air freight courier service with a hub at the Dayton airport .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Bradley First Air", "tail": "Ottawa"}, {"relation": "Organization based in", "head": "Bradley First Air", "tail": "Canada"}, {"relation": "Located in", "head": "Ottawa", "tail": "Canada"}]


Instruction:
Text: Eastport International of Upper Marlboro , Md. , which has been involved in deep-water recovery of wreckage of the space shuttle Challenger as well as other air crashes , retrieved the recorder last Friday from a depth of 14 , 800 feet with its $5 million ` ` remote recovery vehicle ' ' known as Gemini 6000 .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Eastport International", "tail": "Upper Marlboro , Md."}]


Instruction:
Text: In 1985 , shuttle passengers included Sultan Al-Saud of Saudi Arabia and Rodolfo Neri Vela , a Mexican .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Sultan Al-Saud", "tail": "Saudi Arabia"}]


Instruction:
Text: High winds blew on the east slopes of the Rocky Mountains in Montana , with winds gusting to near 50 mph at Livingston .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Rocky Mountains", "tail": "Montana"}, {"relation": "Located in", "head": "Livingston", "tail": "Rocky Mountains"}, {"relation": "Located in", "head": "Livingston", "tail": "Montana"}]


Instruction:
Text: Folke Nyberg , a professor of urban planning and architecture at the University of Washington , agreed Seattle 's location on the Pacific Rim means it will grow , but disagreed that concentrated downtown growth is good .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Folke Nyberg", "tail": "University of Washington"}, {"relation": "Located in", "head": "Seattle", "tail": "Pacific Rim"}]


Instruction:
Text: Seattle has an ` ` hour-glass ' ' figure , squeezed between Puget Sound and Lake Washington , he said .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Puget Sound", "tail": "Seattle"}, {"relation": "Located in", "head": "Lake Washington", "tail": "Seattle"}]


Instruction:
Text: There are even hopeful signs in Chicago 's schools , branded 14 months ago as the nation 's worst by U.S. Secretary William J. Bennett .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "William J. Bennett", "tail": "U.S."}]


Instruction:
Text: Relative size and the power of the purse are certainly key factors , says Samuel L. Husk , executive director of the Council of Great City Schools .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Samuel L. Husk", "tail": "Council of Great City Schools"}]


Instruction:
Text: Navy spokeswoman Lt. Nettie Johnson was unable to say immediately whether the aircraft had experienced problems from faulty check and drain valves .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Nettie Johnson", "tail": "Navy"}]


Instruction:
Text: The ` ` poison pill , ' ' ruled illegal in November by U.S. District G. Ernest Tidwell , would become effective after a shareholder had acquired 10 percent of the outstanding stock .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "G. Ernest Tidwell", "tail": "U.S."}]


Instruction:
Text: Pemex Director Francisco Rojas told a news conference Wednesday that the production of crude oil , gasoline and petrochemicals had returned to normal .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Francisco Rojas", "tail": "Pemex"}]


Instruction:
Text: The government news agency Notimex reported later that leaders of the union 's locals had designated Ricardo Camero Cardiel , a local leader and senator from the northeastern city of Ciudad Madero , the union 's new secretary-general .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Ricardo Camero Cardiel", "tail": "Ciudad Madero"}]


Instruction:
Text: Details of the ` ` friendly ' ' tender offer for Aussedat-Rey SA , Europe 's leading manufacturer of photocopy paper , were not disclosed .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Aussedat-Rey SA", "tail": "Europe"}]


Instruction:
Text: International Paper spokeswoman Ann Silvernail said that under French law the company was barred from releasing details pending government approval .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Ann Silvernail", "tail": "International Paper"}]


Instruction:
Text: GIESSEN , West Germany ( AP )
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "GIESSEN", "tail": "West Germany"}, {"relation": "Organization based in", "head": "AP", "tail": "GIESSEN"}, {"relation": "Organization based in", "head": "AP", "tail": "West Germany"}]


Instruction:
Text: While Minox is struggling , the Leica company in nearby Wetzlar , and Rollei in Braunschweig , report business has been good over the past year .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Leica company", "tail": "Wetzlar"}, {"relation": "Organization based in", "head": "Rollei", "tail": "Braunschweig"}]


Instruction:
Text: Leica spokesman Hans Guenther von Zydowitz told the AP company officals estimate last year 's sales at about $60.6 million , but he declined to estimate profits .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Hans Guenther von Zydowitz", "tail": "Leica"}]


Instruction:
Text: Analyst Scott Hinton of Elders Futures Inc. said the copper market seemed unsinkable , even though prices have fallen from the record highs reached in early December .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Scott Hinton", "tail": "Elders Futures Inc."}]


Instruction:
Text: ` ` The decision to sell these two newspapers was not an easy one , ' ' said James K. Batten , Knight-Ridder president and chief executive officer .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "James K. Batten", "tail": "Knight-Ridder"}]


Instruction:
Text: Many communities running out of landfill space are eager to ship their bulky , plastic garbage to the Middletown plant , called Eaglebrook East , a branch of Eaglebrook Plastics Inc. of Chicago .
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Eaglebrook Plastics Inc.", "tail": "Chicago"}]


Instruction:
Text: BEIRUT , Lebanon ( AP )
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "BEIRUT", "tail": "Lebanon"}, {"relation": "Organization based in", "head": "AP", "tail": "BEIRUT"}, {"relation": "Organization based in", "head": "AP", "tail": "Lebanon"}]


Instruction:
Text: Text of the statement issued by the Organization of the Oppressed on Earth claiming U.S. Marine Lt. William R. Higgins was hanged.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "William R. Higgins", "tail": "U.S."}]


Instruction:
Text: In the name of God , the Merciful , the Compassionate , Since criminal America and the Zionist enemy did not take our decision to execute American spy Higgins seriously , and since Sheik Abdul Karim Obeid and his two brethren were not freed by the specified deadline out of disdain for our ultimatum , the life of Higgins and our sacred sanctities , and to implement God 's just will , the execution of American spy Higgins has been carried out by hanging at 3 p.m. this Monday afternoon 28 Zul Hijja , 1409 Hegira , which coincides with July 31 , 1989 A.D. He will be an example for those who fear the day of reckoning.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Higgins", "tail": "America"}, {"relation": "Live in", "head": "Higgins", "tail": "America"}, {"relation": "Live in", "head": "Higgins", "tail": "America"}]


Instruction:
Text: ` ` The old bugaboo is where this baby is going to hit , ' ' said John Jamison , a National Weather Service meteorologist in Galveston.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "John Jamison", "tail": "National Weather Service"}, {"relation": "Organization based in", "head": "National Weather Service", "tail": "Galveston."}]


Instruction:
Text: Pat Epps and other members of the Greenland Expedition Society suffered hunger , cold and sunburn in the hunt for the ` ` lost squadron , ' ' eight aircraft which crash landed in Greenland in 1942.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Pat Epps", "tail": "Greenland Expedition Society"}]


Instruction:
Text: Vaughan , a dog musher and Army Air Force officer , was sent by dogsled in 1942 to make sure top-secret bombsights on the bombers were destroyed or brought back.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Vaughan", "tail": "Air Force"}]


Instruction:
Text: ` ` What we have witnessed , in the Israeli retaliation in kind for the kidnapping of their people , ( is ) that violence truly does beget violence and that I hope the United States will use this opportunity for reconciliation rather than retaliation , ' ' Mrs. Say said in an interview from her home near Cadiz in western Kentucky.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Mrs. Say", "tail": "Kentucky."}, {"relation": "Located in", "head": "Cadiz", "tail": "Kentucky."}]


Instruction:
Text: NEW ORLEANS ( AP )
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "AP", "tail": "NEW ORLEANS"}]


Instruction:
Text: Pacific Marine Inc. of Houston , was about 15 miles east of Grand Isle.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Pacific Marine Inc.", "tail": "Houston"}]


Instruction:
Text: ` ` Right now , the fire season is just starting to gear up , ' ' said Sandi Sacher , spokeswoman at the federal government 's wildfire command post in Boise , Idaho.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Boise", "tail": "Idaho."}]


Instruction:
Text: By year 's end , 6 million acres had burned in the West and Alaska , making 1988 the worst fire season in 30 years , and , in terms of firefighting resources committed , the most expensive in U.S. history , Sacher said.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "West", "tail": "U.S."}, {"relation": "Located in", "head": "Alaska", "tail": "U.S."}]


Instruction:
Text: ` ` That original one was knocked down for a reason by the tanks , and I presume this one was knocked down for the same reason , ' ' Santa Monica artist Tom Van Sant said Monday after the 23-foot-tall statue was found crushed and broken in pieces.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Tom Van Sant", "tail": "Santa Monica"}]


Instruction:
Text: ` ` He is the same easy-going , soft-spoken , self-effacing man we knew as governor of New Hampshire , ' ' said Virginia Gov. Gerald Baliles , a Democrat.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Gerald Baliles", "tail": "Virginia"}]


Instruction:
Text: Bush , who acknowledged that Sununu was ` ` not quiet and retiring ' ' also had words for Virginia 's Baliles , who was stepping down after a year as chairman of the association.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Baliles", "tail": "Virginia"}]


Instruction:
Text: In May , the Bush administration and the 12-nation European Community reached an interim agreement that allowed resumption of sales of about 15 percent of the $100 million in U.S. beef exports to Europe.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Bush", "tail": "U.S."}, {"relation": "Organization based in", "head": "European Community", "tail": "Europe."}]


Instruction:
Text: In a travel advisory issued Monday , the State Department said there have been ` ` a few instances of attacks on tourists ' ' in Kenya , particularly ` ` along the coast south of Mombasa and in remote areas of the country , including some national parks.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Mombasa", "tail": "Kenya"}]


Instruction:
Text: With China 's crackdown on the democracy movement , ` ` the truth is finally coming out of the cruel nature of communism , ' ' said Shaw Yu-ming , director-general of Government Information , at the opening of Taiwan 's new downtown Washington information center.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Shaw Yu-ming", "tail": "Government Information"}]


Instruction:
Text: The Taiwan information center provides background and research material on China at a suite of offices in Washington 's National Press Building , where several hundred U.S. and international news organizations also have bureaus.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "National Press Building", "tail": "Washington"}]


Instruction:
Text: The drug is an active ingredient in products sold under the trade name Phenergan , made by Wyeth-Ayerst Laboratories of Philadelphia.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Organization based in", "head": "Wyeth-Ayerst Laboratories", "tail": "Philadelphia."}]


Instruction:
Text: Heavier rainfall during the 6 hours ending at 2 a.m. EDT included 1 -LCB- inches at Cape Hatteras , N.C. , and almost an inch at Jacksonville , N.C. , and Dodge City , Kan.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Cape Hatteras", "tail": "N.C."}, {"relation": "Located in", "head": "Jacksonville", "tail": "N.C."}, {"relation": "Located in", "head": "Dodge City", "tail": "Kan."}]


Instruction:
Text: Temperatures around the nation at 3 a.m. EDT ranged from 44 degrees at Klamath Falls , Ore. , to 91 degrees at Yuma , Ariz.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Klamath Falls", "tail": "Ore."}, {"relation": "Located in", "head": "Yuma", "tail": "Ariz."}]


Instruction:
Text: About 1 , 000 soldiers from Fort Lewis , Wash. , were summoned to Oregon for on-the-job training before being thrown on to the front lines.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Fort Lewis", "tail": "Wash."}]


Instruction:
Text: ` ` We 're in for a long haul , ' ' said Dave Olson of the Payette National Forest in Idaho , where more than 200 fires continued to burn.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Dave Olson", "tail": "Idaho"}, {"relation": "Located in", "head": "Payette National Forest", "tail": "Idaho"}]


Instruction:
Text: In northeastern Oregon , at least five major fires and several smaller ones burned across 60 , 000 acres , forcing the evacuation of some rural homes and threatening the watershed for the city of La Grande , authorities said.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "La Grande", "tail": "Oregon"}]


Instruction:
Text: About 2 , 900 firefighters were battling blazes in the Wallowa-Whitman and the Malheur national forests near the towns of Baker , Unity , Enterprise and John Day , said Forest Service spokesman Mike Ferris.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Mike Ferris.", "tail": "Forest Service"}]


Instruction:
Text: Also on the GOP ballot are insurance broker David Fleischer and former North Miami Mayor John Stembridge.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "John Stembridge.", "tail": "North Miami"}]


Instruction:
Text: ` ` NRC has a broad programmatic concern that the pressure to meet unrealistic schedule milestones may leave DOE insufficient time to plan and to execute proper technical information-gathering activities , ' ' said Robert Bernero , chief of waste disposal for the commission.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Robert Bernero", "tail": "NRC"}]


Instruction:
Text: Khmer Rouge leader Khieu Samphan had raised objections to the investigation mission and other aspects of today 's agreements.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Work for", "head": "Khieu Samphan", "tail": "Khmer Rouge"}]


Instruction:
Text: On Monday , one man was lost from an oil rig off Grand Isle , La. , as the storm moved in.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Located in", "head": "Grand Isle", "tail": "La."}]


Instruction:
Text: Port Arthur Mayor Malcolm Grant asked the 800 residents of Sabine Pass to evacuate the coastal community just west of the Louisiana line , citing the likelihood of high water closing the only highway between the town and Port Arthur.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Malcolm Grant", "tail": "Port Arthur"}, {"relation": "Live in", "head": "Malcolm Grant", "tail": "Port Arthur."}]


Instruction:
Text: ` ` If they tell us to get out , we get out , ' ' said Lutie Dyson , 62 , who with her husband and about 65 others took shelter in a school in Lake Charles , La.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['Organization based in', 'Located in', 'Live in', 'Work for', 'Kill']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "Live in", "head": "Lutie Dyson", "tail": "Lake Charles"}, {"relation": "Live in", "head": "Lutie Dyson", "tail": "La."}, {"relation": "Located in", "head": "Lake Charles", "tail": "La."}]


Instruction:
Text: here for video on Sarah John Glover Sarah Glover was born in 1786, in The Close. In 1811, her father became Curate of St Lawrence, where she and her sister led the unaccompanied singing. In trying to teach a young Sunday School teacher the tunes, so that he could teach the children, she hit upon her system of notation, in which DOH is always the first note of the scale, RAY the second, and so forth. This was called the Norwich Sol-fa.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of death", "head": "John Glover", "tail": "Norwich"}]


Instruction:
Text: Mohamadou Bayero Fadil was born on 19 December 1960 in Garoua , capital of the North Province of Cameroon. A businessman, he is chief executive officer CEO of Group Fadil, an agro-industrial group prominent within Central Africa, which operates in several sectors including soap, oil extraction, tourism, livestock, and new information technologies. The company was founded by M. Fadil is father in 1944.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of birth", "head": "Mohamadou Bayero Fadil", "tail": "Garoua"}]


Instruction:
Text: George Feyer  died just six days before his 93rd birthday, at Lenox Hill Hospital in Manhattan's Upper East Side . He was survived by his son (who lives in San Francisco), three grandsons, and second wife (who died within the year after he died).
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of death", "head": "George Feyer ", "tail": "Upper East Side"}]


Instruction:
Text: Joseph Chappell Hutcheson, Jr. 1879-1973 was a federal judge on the United States Court Bachelor of Laws Appeals for the Fifth Circuit.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education degree", "head": "Joseph Chappell Hutcheson, Jr.", "tail": "Bachelor of Laws"}]


Instruction:
Text: Daniel Foley missed the conversation to ensure that another try was needed. Next, Tynan heroically leapt over Leinster backrow Caelan Doris. That confirmed the momentum shift as Blackrock slipped into survival mode; the Roscrea people sensed the chance, the once in a lifetime chance. The monstrous teenagers on the field, however, are unaware of history, they just knew they have the south Dublin boys number.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of death", "head": "Daniel Foley", "tail": "Blackrock"}]


Instruction:
Text: his spell at Durham University, Sid Waddell joined Granada Television before moving to Yorkshire where he presented the Indoor League show which included darts. In 1976 he moved to the BBC to become one of the commentators on the fir St John's College, Cambridge World Professional Darts Championship in 1978. Other work included The Russell Harty Show, producing Whicker is Women which starred Alan Whicker and writing 10 episodes of the successful children is series Jossy is Giants.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Sid Waddell", "tail": "St John's College, Cambridge"}]


Instruction:
Text: George Gabin studied Art Students League of New York at the Brooklyn Museum Art School in Brooklyn, New York, from 1949-54. He also studied at the Art Students League in New York City from 1950-54. His teachers included Reginald Marsh, Ivan Olinsky, and Will Barnet.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "George Gabin", "tail": "Art Students League of New York"}]


Instruction:
Text: James William Wallack (c. 1794--1864) was an Anglo-American actor and manager, born in London , and brother of Henry John Wallack.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of birth", "head": "James William Wallack", "tail": "London"}]


Instruction:
Text: is a graduate of St. Daniel John Snyder is University in Collegeville, Minnesota with a Bachelor of Arts degree in Accounting. A Certified Fraud Examiner, Jeff has also previously held CPA, Securities FINRA and Insurance licenses.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education degree", "head": "Daniel John Snyder", "tail": "Bachelor of Arts"}]


Instruction:
Text: We Austin L come to the home page Bachelor of Science the Department of Computer Science and Information Technology. If you are a prospective student, the links on this page will provide you with much of the information that you need. We welcome on-line, transfer, and second-degree students. If you need more information, please contact our office at 931-221-7840 or email Dr. Bruce Myers, the Chair of the Department.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education degree", "head": "Austin L", "tail": "Bachelor of Science"}]


Instruction:
Text: Jonathan Green is an English journalist and author, born in Bury St Edmunds , he lives in Massachusetts with his wife.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of birth", "head": "Jonathan Green", "tail": "Bury St Edmunds"}]


Instruction:
Text: Margaret Dingeldein attended medical Merced High School at the University of California, San Francisco, and on graduating became an anesthesiology resident at UCSF Medical Center.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Margaret Dingeldein", "tail": "Merced High School"}]


Instruction:
Text: Aristides Brezina (4 May 1848 -- 25 May 1909) was an Austrian mineralogist born in Vienna . In 1872 he graduated from the University of TA14bingen, and afterwards taught crystallography at the University of Vienna. In 1878 he succeeded Gustav Tschermak (1836-1927) as custodian of the meteorite collection at Vienna, and from 1889 until 1896 he was director of the Mineralogisch-Petrographische Abteilung (Department of Mineralogy-Petrography).
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of birth", "head": "Aristides Brezina", "tail": "Vienna"}]


Instruction:
Text: Alan Schriesheim was born in 1930 in Far Rockaway (Queens), New York. He graduated from Far Rockaway High School in 1948 where he played football. Schriesheim graduated from Penn State in 1954 with a Ph.D. in chemistry, having earned his bachelor's degree from The Polytechnic Institute of New York University (known then as Brooklyn Polytechnic Institute) in 1951. He was the first person in his family to attend college, his father had a 6th grade education and was a furntiture store manager.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Alan Schriesheim", "tail": "Far Rockaway High School"}]


Instruction:
Text: William P . Brown is an ordained minister in the Presbyterian Church USA, author, biblical theologian, and the William Marcellus McPheeters Pr Bachelor of Arts essor of Old Testament at Columbia Theological Seminary.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education degree", "head": "William P", "tail": "Bachelor of Arts"}]


Instruction:
Text: Otto Goodell William H. Kelsey November 11, 1852 - August 20, 1934 was an American lawyer and politician. He was born on November 11, 1852, in Rochester, Monroe County, New York, the son of Wisconsin State Senator Charles S. Kelsey born 1822 and Lucretia Parson Bacon Kelsey died 1868. He became a printer, then studied law, was admitted to the bar in 1875, and practiced law in Geneseo , Livingston County, New York.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of death", "head": "William H. Kelsey", "tail": "Geneseo"}]


Instruction:
Text: Laurie Metcalf as Dr. Jenna James Patrick Leamy Grace And Frankie * Netflix * Skydance Productions for Netflix Lily Tomlin as Frankie Unbreakable Kimmy Schmidt * Netflix * Universal Television, Little Stranger, Inc., 3 Master of Arts  Entertainment and Bevel Gears for Netflix Ellie Kemper as Kimmy Schmidt Outstanding Lead Actor In A Limited Series Or Movie All The Way * HBO * HBO Films in association with Amblin Television, Tale Told Productions, Moonshot Entertainment and Everyman Pictures
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education degree", "head": "James Patrick Leamy", "tail": "Master of Arts "}]


Instruction:
Text: George Perkins Merrill (May 31, 1854 Androscoggin County / Auburn city , Maine -- August 15, 1929) was an American geologist.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of birth", "head": "George Perkins Merrill", "tail": "Androscoggin County / Auburn city"}]


Instruction:
Text: Robert Humphrey was born in Perryton, Texas, in 1947, and graduated high school in 1965. He pursued a degree in Music Education at West Texas State University and The University of Kansas, complimenting his education in Business at Central State University (Oklahoma), and Methodist College (Fayetteville, NC) where he was a broadcaster with WQTI-FM radio.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Robert Humphrey", "tail": "Central State University"}]


Instruction:
Text: NEW YORK AP - William H. McNeill , the prize-winning scholar who wove the stories of civilizations worldwide into the landmark The Rise of the West and helped pioneer the history of disease and epidemics in Plagues and People, has died at age 98. McNeill died Friday at his home in Torrington, Connecticut, according to Steve Koppes, associate news director at the Cornell University of Chicago, where McNeill was a professor emeritus.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "William H. McNeill", "tail": "Cornell University"}]


Instruction:
Text: Born in West Chester, Pennsylvania, Robert Gawthrop III received a ((NAM: B.A.)) from Amherst College in 1964 and a J.D. from Dickinson School Bachelor of Arts Law in 1970. He was in the United States Army Lieutenant, Field Artillery from 1965 to 1967. He was a law clerk, Hon. Lee F. Swope, Harrisburg, Pennsylvania from 1969 to 1970. He was in private practice in West Chester, Pennsylvania from 1970 to 1978. He was an Assistant district attorney of West Chester, Pennsylvania from 1971 to 1978. He was an Assistant district attorney of Wayne County, Pennsylvania from 1976 to 1977. He was a judge on the Court of Common Pleas, Chester County, Pennsylvania from 1978 to 1988. He was an Adjunct professor, Dickinson School of Law from 1981 to 1982.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education degree", "head": "Robert Gawthrop III", "tail": "Bachelor of Arts"}]


Instruction:
Text: Leigh Turner . Transnational Medical Travel: Ethical Dimensions University of Cambridge Global Healthcare. Cambridge Quarterly of Healthcare Ethics 2013; 22, 2: 170-180. Victoria Casey, Valorie Crooks, Jeremy Snyder, and Leigh Turner. You are dealing with an emotionally charged individual...: an industry perspective on the challenges posed by medical tourists informal caregiver-companions. Globalization and Health 2013; 9: 31.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Leigh Turner", "tail": "University of Cambridge"}]


Instruction:
Text: Sir John Myres Linton Myres (3 July 1869 in Preston -- 6 March 1954 in Oxford) was a British archaeologist. He conducted excavations in Cyprus in 1904. He became the first Wykeham Professor of Ancient History, at the University of Oxford, in 1910, having been Gladstone Professor of Greek and Lecturer in Ancient Geography, University of Liverpool from 1907. He contributed to the British Naval Intelligence Division Geographical Handbook Series that was published during the Second World War, and to the noted 11th edition of the EncyclopAdia Britannica (1910--1911). He highly influenced the British-Australian archaeologist Vere Gordon Childe.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of birth", "head": "John Myres", "tail": "Preston"}]


Instruction:
Text: diligent in your coaching areas. Laurie Fisher has also held discussions about coaching positions at three other Canberra, Australia n Super Rugby sides but his heart lies with the Brumbies. I am hopeful we can come to some arrangement and I do not think that would be too difficult, said Fisher.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of birth", "head": "Laurie Fisher", "tail": "Canberra, Australia"}]


Instruction:
Text: Joshua Mathiot was elected as a Whig to the Twenty-seventh Congress (March 4, 1841-March 3, 1843). Grand worthy patriarch of the Sons of Temperance in Ohio, and while attending a temperance convention at Sandusky contracted cholera, from which he died in Newark , Ohio, July 30, 1849. He was interred in Cedar Hill Cemetery.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of death", "head": "Joshua Mathiot", "tail": "Newark"}]


Instruction:
Text: Gordon Lockhart Bennett , OC October 10, 1912 - February 11, 2000 was a Canadian teacher, politician and the 21st Lieutenant Governor of Prince Edward Island. Born in Charlottetown, Canada Prince Edward Island, he received a Bachelor of Science in 1937 and a Master of Science in Chemistry in 1947 from Acadia University. He started to teach in a school and joined the faculty of the department of Chemistry at Prince of Wales College in 1939.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of birth", "head": "Gordon Lockhart Bennett", "tail": "Charlottetown, Canada"}]


Instruction:
Text: After the war, Peter Green attended Trinity College of Cambridge University. He subsequently wrote historical novels and worked as a journalist. In 1963 he and his family moved to the Greek island of Lesbos, where he was a translator, and then to Athens, where he was recruited to teach classics for the College Year in Athens.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Peter Green", "tail": "Trinity College"}]


Instruction:
Text: community development finance and policy, Martin Daniel Eakes currently serves on the Ford Foundation Board of Trustees, the Bank of America National Community Advisory Council and the Guilford Davidson College Board of Trustees.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Martin Daniel Eakes", "tail": "Davidson College"}]


Instruction:
Text: Nora Holt returned to the United States in 1938 and settled in Los Angeles County / Los Angeles city Angeles. She taught music for several years, then returned to New York, where she was the first music critic for the Amsterdam News and later the New York Courier. In 1945 Holt became the first African American member of the Music Critics Circle of New York. She produced and directed Concert Showcase, a radio show on WLIB in New York in the 1950s and 1960s.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of death", "head": "Nora Holt", "tail": "Los Angeles County / Los Angeles city"}]


Instruction:
Text: Thomas Albert born December 14, 1948 is an American composer and educator. Thomas Albert attended the public schools of Lebanon, Pennsylvania and Wilson, North Carolina. In 1970, he received the degree A.B. Magna Cum Laude from Atlantic Christian College now Barton College , where he studied composition with William Duckworth. He received the M.Mus. 1972 and D.M.A. 1974 in composition from the University of Illinois at Urbana-Champaign, studying with Paul Martin Zonn and Ben Johnston.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Thomas Albert", "tail": "Barton College"}]


Instruction:
Text: SHOWS I am Not Tom Thomas Pope , You Are All Tom Pope. The Old Police Station, Jersey, 2015 So it Goes. George and Jorgen, Clerkenwell, London , 2013 The Escapades of the Higher Man, The Glynn Vivian Art Galley Swansea, 2010 2015 LUMEN, New York
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of death", "head": "Thomas Pope", "tail": "Clerkenwell, London"}]


Instruction:
Text: equally diveded among children: Luke, William H , John, Peterfield, Alexander Kent, Candace Arnold, Mary Posey, and Caty Hendricks.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of death", "head": "William H", "tail": "Kent"}]


Instruction:
Text: meaner streets of industrial Chicago. Bob Miller  attended Roman Catholic schools. He graduated from Bishop Gorman High School in 1963 with honors, and from Santa Clara University in 1967, earning a degree in political science. He received his J.D. degree from Loyola Law School in Los Angeles, California.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Bob Miller ", "tail": "Bishop Gorman High School"}]


Instruction:
Text: Born in Brunswick County, Virginia, David Dortch Warriner received a ((NAM: B.A.)) from the University Bachelor of Arts North Carolina in 1951 and an LL.B. from the University of Virginia School of Law in 1957. He was in the United States Navy Lieutenant (JG) from 1951 to 1954. He was in private practice in Emporia, Virginia from 1957 to 1974. He was a City attorney of Emporia, Virginia from 1969 to 1974.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education degree", "head": "David Dortch Warriner", "tail": "Bachelor of Arts"}]


Instruction:
Text: Sigmund Zeisler graduated from Northwestern University School of Law University Law School in 1884. In 1885 he married Fannie Bloomfield. The Zeislers had three sons: Leonard, Paul and Ernest.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Sigmund Zeisler", "tail": "Northwestern University School of Law"}]


Instruction:
Text: Fernando Caruncho was born in Madrid, Spain and grew up travelling between Madrid and the southern Spanish province of Andalusia. He first attended the Complutense University of Madrid of Madrid to study philosophy, but learning of the Greek method of teaching in the garden motivated his to transfer to Castillo de Batres School in Madrid where he received a degree in landscape design in 1979. While there he focused on classical Greek and Islamic gardens. Caruncho explicitly refuses to describe himself as a paisajista, a landscape designer; he instead refers to himself as a jardinero, a gardener, citing that even ``Capability'' Brown called himself a gardener. He views the garden, not as a landscape, but as a person with its own personality and as a member of the family; a protector of the residence.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Fernando Caruncho", "tail": "Complutense University of Madrid"}]


Instruction:
Text: James Lebbie is a touring and teaching professional and a member of the Sierra Leone PGA. He is Sierra Leone is most successful professional golfer. He played in many tournaments on Europe is second tier Challenge Tour, mainly those held in Africa, recording a solitary victory in the 1992 Nigerian Open. He has also won the Sierra Leone Open many times.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "place of birth", "head": "James Lebbie", "tail": "Sierra Leone"}]


Instruction:
Text: Ben Okri , born March 15, 1959, Minna, Nigeria, Nigerian novelist, short-story writer, and poet who used magic realism to convey the social and political chaos in the country University of Essex his birth.
【Relation Extraction】From the given text, extract the possible head entities (subjects) and tail entities (objects) and give the corresponding relation triples. The relations are ['place of death', 'place of birth', 'education degree', 'education institution']. Output the result in json[{'relation':'', 'head':'', 'tail':''}, ].
Answer:

[{"relation": "education institution", "head": "Ben Okri", "tail": "University of Essex"}]