text:
As Caravan of Migrants Begins Entry at U.S.-Mexico Border, Trump Admin Attacks Legal Asylum Process
Nicole Ramos
director of the Border Rights Project of Al Otro Lado, a project that works with asylum seekers in Tijuana, Mexico, who want to present themselves to U.S. authorities.
Tristan Call
volunteer with Pueblo Sin Fronteras, or People Without Borders.
A standoff continues on the U.S.-Mexico border, where scores of asylum seekers are attempting to cross into the United States after taking part in a month-long caravan that began more than 2,000 miles away in the southern Mexican state of Chiapas. Many of the caravan participants are migrants fleeing violence in Honduras, Guatemala and El Salvador. Around 100 have been accepted for processing, but scores remain camped out by the border near San Diego, California, as officials claim the border entry point has limited capacity. President Trump and Attorney General Jeff Sessions have attacked the migrants in statements and tweets. "It's very clear that President Trump and Attorney General Sessions do not understand this section of federal law," says attorney Nicole Ramos, director of the Border Rights Project of Al Otro Lado, who represents members of the caravan. "The caravan members that are camped out at the border are trying to access a legal process which has existed for decades." We speak with Ramos, who is in Tijuana, Mexico, and with Tristan Call, a volunteer with Pueblo Sin Fronteras, or People Without Borders, just back from spending time with the caravan.
StoryOct 09, 2019Julián Castro Slams Trump's "Deranged" Immigration Policies After Escorting Asylum Seekers to Border
NERMEEN SHAIKH: A standoff continues on the U.S.-Mexico border, where scores of asylum seekers are attempting to cross into the United States after taking part in a month-long caravan that began more than 2,000 miles away in the southern Mexican state of Chiapas. Many of the caravan participants are migrants fleeing violence in Honduras, Guatemala and El Salvador. The caravan is organized annually by the group Pueblo Sin Fronteras, or People Without Borders. It made international headlines this year, largely thanks to President Trump. In one tweet, Trump wrote, quote, "Getting more dangerous. 'Caravans' coming." During a rally in Michigan on Saturday, Trump again criticized the caravan.
PRESIDENT DONALD TRUMP: We believe that a strong nation must have strong borders.
CROWD: Build the wall! Build the wall! Build the wall! Build the wall! Build the wall! Build the wall! Build the wall!
PRESIDENT DONALD TRUMP: Are you watching that mess that's going on right now with the caravan coming up? Are you watching this? And our laws are so weak, they're so pathetic, given to us by Democrats.
NERMEEN SHAIKH: Under international law, the United States must allow foreigners seeking asylum to enter the country. But supporters of the caravan say border authorities have been slow to take in members of the caravan seeking asylum. Around a hundred asylum seekers have been accepted for processing, but scores remain camped out by the border near San Diego, California. This is caravan member Nefi Hernández from Honduras.
NEFI HERNÁNDEZ: [translated] We hope for understanding. We hope for a bit of heart, so U.S. authorities can understand that we come to seek asylum from our countries. We can't return. In my case, I can't return to my country, because I'm in danger of losing my life, not just mine, but those of my family, as well.
AMY GOODMAN: On Wednesday, Attorney General Jeff Sessions announced he would send an additional 35 assistant U.S. attorneys and 18 immigration judges to the U.S.-Mexico border.
ATTORNEY GENERAL JEFF SESSIONS: We are not going to let this country be overwhelmed. People are not going to caravan or otherwise stampede our border. We need legality and integrity in the system. People should wait their turn, ask to apply lawfully before they enter our country. So we're sending a message worldwide: Don't come illegally. Make your claim to enter America in the lawful way, and wait your turn.
AMY GOODMAN: For more, we're joined by two guests. In Atlanta, Tristan Call is a volunteer with Pueblo Sin Fronteras, which is People Without Borders, just back from spending time with the caravan in Mexico. And joining us on the phone from the border, from Tijuana, Mexico, Nicole Ramos is director of the Border Rights Project of Al Otro Lado, a project that works with asylum seekers who want to present themselves to U.S. authorities.
We welcome you both to Democracy Now! And we want to begin with Nicole. Tell us the latest. You have President Trump constantly railing against this caravan, demanding that Mexico break it up before it got to the border, as he's demanded they pay for the border wall. The caravan has arrived at the border, maybe fewer people than was originally intended. And you've got what? More than 25 people who have already processed? Explain the situation.
NICOLE RAMOS: The caravan members that are camped out at the border are trying to access a legal process which has existed for decades. It's very clear that President Trump and Attorney General Sessions do not understand this section of federal law, under Title 8, Section 1225 of the United States Code. This is not illegal migration. This is the legal process, which allows an asylum seeker to present themselves at a port of entry to an immigration officer, indicate that they have a fear of return, after which time they are to be granted an interview with an asylum officer. So, their commentary that this is a stampede, this is illegal migration, this is not waiting their turn—this is the process.
NERMEEN SHAIKH: And what explanation, Nicole, have you received for why there have been such delays in the processing of these asylees or people seeking asylum, not having been granted it?
NICOLE RAMOS: U.S. Customs and Border Protection has indicated that they lack the capacity at the port of entry to process these asylum seekers. However, they were aware that this caravan was traveling for now almost a month, and the numbers have significantly diminished [inaudible] 200 presenting themselves. And what we have is either a failure to prepare or a refusal to prepare. And I would argue it is the latter, given that Customs and Border Protection is the largest law enforcement agency in the United States.
AMY GOODMAN: And what do you make of Jeff Sessions saying he's sending more lawyers and judges to the border right now, and talking about people can't overrun the border?
NICOLE RAMOS: People are not trying to overrun the border. It's a very small group when you consider all the people that migrate in a year. And the fact that he's sending more attorneys and more judges to adjudicate the cases, that's assuming that people first get past the first step, which is an interview with an asylum officer. So, his allocation of resources, his calculus, is two steps ahead, which again indicates to me that, unfortunately, Attorney General Sessions does not understand immigration law very well.
NERMEEN SHAIKH: And, Nicole, you're in Tijuana, Mexico. Could you describe what the scene is there at the border?
NICOLE RAMOS: It's a desperate situation. It's hopeful in the sense that people, you know, they know that they are not going to be camped out forever. They don't know how long they will be waiting. But it is a desperate situation to come so far, and coming to the U.S. because we are a nation of laws, because we do put ourselves out on the world stage as a nation that fights for human rights and respects human rights, and to get to the border and have the port of entry door literally closed in their faces. And I've been down to the gate to the U.S., and it is almost all but blocked off, except for one tiny door. And so that, in itself, is very heartbreaking. But it's a testament to the desperation that the people feel and the fear that is driving them to flee their countries, is that they're willing to go to a place that they know may be hostile to them, because it is the only option.
AMY GOODMAN: Let's turn to Fox News host Tucker Carlson on the arrival of the caravan at the U.S.-Mexico border, where he attacked you, Nicole Ramos, by name.
TUCKER CARLSON: The left argues we have no moral right to stop any of them from doing that. Here's attorney Nicole Ramos of Tijuana denouncing the U.S. government as criminal for trying to enforce our own federal law. Watch.
NICOLE RAMOS: The message for Customs and Border Protection: Stop rejecting asylum seekers who try to present themselves at the port of entry. You know what you're doing. You know you turn people away. You complain that they are breaking the law by entering illegally. You are breaking the law, and you are forcing them to break the law. That's why we have caravans.
TUCKER CARLSON: Yeah, that's definitely someone you want in control of our public policy, screaming into a bullhorn.
AMY GOODMAN: Your response, Nicole Ramos, live on the border, to Tucker Carlson of Fox News?
NICOLE RAMOS: Well, I'm using a bullhorn because I'm at a press conference and it's a pretty chaotic scene, so that the crowd could hear me. I don't normally walk around with a bullhorn.
Customs and Border Protection has a history, dating back years, of rejecting asylum seekers who try to present themselves and follow the legal process. I have been collecting data on illegal turnbacks in Tijuana at the port of entry since December of 2015. I have accompanied hundreds of asylum seekers. And of those hundreds that I've accompanied, there are countless times that a CBP officer has told the client that I'm with that they cannot seek asylum at a port of entry, that they have to go to the embassy in their home country, or the consulate, which just—it's not true.
That the law is that it allows someone to go to a port of entry. And it forces people who don't have the support of advocates to try to enter through irregular means. These are people who are trying to follow the law. And you have federal law enforcement officers who are breaking the law, and who are so brazen in their disregard for the law that they will do it in front of an attorney, an officer of the court. And this history is well documented in the human rights reports of Amnesty International, Human Rights Watch, Human Rights First. And it's the subject of litigation that our organization has filed against DHS.
NERMEEN SHAIKH: Well, I want to turn to some of the people who have been seeking asylum. Channel, a 28-year-old Honduran trans woman, for instance, said she had no option but to leave her country because of the discrimination she faced at home due to her sexual orientation.
CHANNEL: [translated] I don't think I'll ever return to my country, because I don't think I'd survive to tell my story. I have already survived an attack, and it's very difficult. I've already been between life and death. I was in a coma for three days, and I wouldn't want that for me.
In the United States, I see myself sleeping calmly. I see myself sleeping better, not only myself, but my friends, where we are able to obtain more respect, where there is no bullying against us, where people don't shout at us, where the decision of each person is truly respected, such as the decision of being trans women.
NERMEEN SHAIKH: So, Tristan Call, you're a volunteer with People Without Borders. You've just returned from spending time with the caravan in Mexico. Could you talk about the conditions that people seeking asylum are fleeing?
TRISTAN CALL: Yeah. I think one of the most important things to understand in why people traveled in a caravan together is not just that they're people who have been displaced by tremendous trauma and violence in the countries that they're coming from, but also traveling through Mexico is an incredibly dangerous thing. It's become more and more dangerous because of the forms of criminalization that are getting replicated from the U.S. model in Mexico. And so, the amounts of violence, of kidnapping, of assaults by Mexican officials within Mexico against migrants who are en route, is one of the main reasons why they've decided to band together for their own security.
Coming from Honduras especially, I think it's important to understand that there's a regional crisis that's going on in Central America, where larger and larger numbers of people are being expelled through violence and discrimination, in Honduras especially through political violence after the continuation in power of Juan Orlando Hernández, who most people in Honduras understand is staying in power through an electoral fraud.
AMY GOODMAN: Nicole Ramos, what happens next on the border?
NICOLE RAMOS: Apart from ensuring that the caravan members are able to present themselves in accordance with U.S. law, what happens next is unclear, because for the last several weeks, months, we've had asylum seekers camped out in front of the port of entry. So what's happening to the caravan is the continuation of an existing phenomenon, where Customs and Border Protection will artificially set a limit for how many people it will accept a day. It won't process asylum seekers at night. It's indicated to Mexican authorities that they don't process people on the weekends. And so, what they're doing is they're setting these artificial parameters that don't exist anywhere in our federal regulations.
And one of the strengths of the caravan is that it's allowing asylum seekers to come out of the shadow in Mexico. Not only are we dealing with the caravan members on the ground, but now we have other asylum seekers who are coming to the camp because they know attorneys are there, and they're asking questions, and they're talking about their own experiences of being turned away after trying to present themselves multiple times. And so, we're going to be continuing to collect that data. We're going to continue to advocate for those individuals after the caravan leaves, and we're going to continue doing this work. We may not have a camp, but we are going to sit outside of the port of entry until they process every single one of them.
AMY GOODMAN: Well, we want to thank you both for being with us, Nicole Ramos of the Border Rights Project of Al Otro Lado, which means "The Other Side," and Tristan Call with the group People Without Borders.
This is Democracy Now! When we come back, the acclaimed writer, activist Arundhati Roy. Stay with us.
Arundhati Roy's Latest Novel Takes on Fascism, Rising Hindu Nationalism in India & Abuses in Kashmir
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Julián Castro Slams Trump's "Deranged" Immigration Policies After Escorting Asylum Seekers to Border


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MaltParser

Modified: May 5 2014

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Get MaltParser

Download

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Introduction

Installing MaltParser

User guide

Options (short version)

Options (long version)

JavaDoc

Resources

Pre-trained models

Publications

CoNLL Shared Task

MaltEval

Contact

Contact

User guide

The user guide consists of the these sections:

Start using MaltParser

Controlling MaltParser

Configuration

Input and output format

Parsing algorithm

Feature model

Learner

Prediction strategy

Parsing with partial trees

Propagation

MaltParser API

MaltParser optimization

References

Start using MaltParser

This section contains a short guide to get familiar with MaltParser. We start by running MaltParser without any arguments
by typing the following at the command line prompt (it is important that you are in the maltparser-1.8 directory):

prompt> java -jar maltparser-1.8.jar

This command will display the following output:

-----------------------------------------------------------------------------
                          MaltParser 1.8
-----------------------------------------------------------------------------
         MALT (Models and Algorithms for Language Technology) Group
             Vaxjo University and Uppsala University
                             Sweden
-----------------------------------------------------------------------------

Usage:
   java -jar maltparser-1.8.jar -f <path to option file> <options>
   java -jar maltparser-1.8.jar -h for more help and options

help                  (  -h) : Show options
-----------------------------------------------------------------------------
option_file           (  -f) : Path to option file
-----------------------------------------------------------------------------
verbosity            *(  -v) : Verbosity level
  debug      - Logging of debugging messages
  error      - Logging of error events
  fatal      - Logging of very severe error events
  info       - Logging of informational messages
  off        - Logging turned off
  warn       - Logging of harmful situations
-----------------------------------------------------------------------------

Documentation: docs/index.html

Here you can see the basic usage and options. To get all available options:

prompt>$ java -jar maltparser-1.8.jar -h

All these options are also described in a short documentation and in a full documentation.

Train a parsing model

Now we are ready to train our first parsing model. In the directory examples/data there are two data files talbanken05_train.conll
and talbanken05_test.conll, which contain very small portions of the Swedish treebank Talbanken05.
The example data sets are formatted according to the CoNLL data format. Note that
these data sets are very small and that you need more training data to create a useful parsing model.

To train a default parsing model with MaltParser type the following at the command line prompt:

prompt> java -jar maltparser-1.8.jar -c test -i examples/data/talbanken05_train.conll -m learn

This line tells MaltParser to create a parsing model named test.mco (also know as a Single Malt configuration file) from the data
in the file examples/data/talbanken05_train.conll. The parsing model gets its name from the configuration name, which is specified
by the option flag -c without the file suffix .mco.
The configuration name is a name of your own choice. The option flag -i tells the parser where to find the input data. The last option flag -m
specifies the processing mode learn (as opposed to parse), since in this case we want to induce a model by using the default
learning method (LIBSVM).

MaltParser outputs the following information:

-----------------------------------------------------------------------------
                          MaltParser 1.8
-----------------------------------------------------------------------------
         MALT (Models and Algorithms for Language Technology) Group
             Vaxjo University and Uppsala University
                             Sweden
-----------------------------------------------------------------------------

Started: Fri May 02 23:45:18 CEST 2014
  Transition system    : Arc-Eager
  Parser configuration : Nivre with allow_root=true, allow_reduce=false and enforce_tree=false
  Oracle               : Arc-Eager
  Data Format          : conllx.xml
.          	      1	      0s	      5MB
.          	     10	      0s	      6MB
           	     32	      0s	      8MB
Creating Liblinear model odm0.liblinear.moo
- Read all training instances.
- Train a parser model using LibLinear.
- Optimize the memory usage
- Save the Liblinear model odm0.liblinear.moo
Learning time: 00:00:01 (1290 ms)
Finished: Fri May 02 23:45:19 CEST 2014

Most of the logging information is self-explaining: it tells you that the parser is started at a certain time and date and that it reads sentences
from a specified file containing 32 sentences. It continues with information about the learning models that are created, in this case only
one LIBSVM model. It then saves the symbol table and all options (which cannot be changed later during parsing) and stores everything in a configuration file
named test.mco. Finally, the parser informs you about the learning time.

Parse data with your parsing model

We have now created a parsing model that we can use for parsing new sentences from the same language. It is important that unparsed sentences are
formatted according to the format that was used during training (except that the output columns for head and dependency relation are missing).
In this case tokens are represented by the first six columns of the CoNLL data format. To parse type the following:

prompt> java -jar maltparser-1.8.jar -c test -i examples/data/talbanken05_test.conll -o out.conll -m parse

where -c test is the name of the configuration (the prefix file name of test.mco), -i examples/data/talbanken05_test.conll tells
the parser where to find the input data, -o out.conll is the output file name, and finally -m parse specifies that the parser should be
executed in parsing mode.

Controlling MaltParser

MaltParser can be controlled by specifying values for a range of different options. The values for these option can be specified in different ways:

Method	Description	Example

Command-line option flag	Uses the option flag with a dash (-) before the option flag and a blank between the option flag and the value	-c test

Command-line option group and option name	Uses both the option group name and the option name to specify the option, with two dashes (--)
before the option group name and one dash (-) to separate the option group name and the option name. The equality sign (=) is used for separating the option and the value.	--config-name=test

Command-line option name	Is a shorter version of Command-line option group and option name and can only be used when the option name is unambiguous. 	--name=test

Option file	The option settings are specified in a option file, formatted in XML.
To tell MaltParser to read the option file the option flag -f is used. Note that command line option settings override the settings
in the option file if options are specified twice.

<?xml version="1.0" encoding="UTF-8"?>
<experiment>
  <optioncontainer>
    <optiongroup groupname="config">
      <option name="name" value="test"/>
    </optiongroup>
  </optioncontainer>
</experiment>

All options are described in a short documentation and a full documentation.

Option file

An option file is useful when you have many options that differ from the default value, as is often the case when you are training a parsing model.

The option file should have the following XML format:

Element	Description

experiment	All other elements must be enclosed by an experiment element.

optioncontainer	It is possible to have one or more option containers, but MaltParser 1.8 only uses the first
option container. Later releases may make use of multiple option containers, for instance, to build ensemble systems.

optiongroup	There can be one or more option group elements within an option container. The attribute groupname
specifies the option group name (see description of all available options).

option	An option group can consist of one or more option. The element option has
two attributes: name that corresponds to an option name and value that is the value of the option. Please consult the description of all
available options to see all legal option names and values.

Here is an example (examples/optionexample.xml):

<?xml version="1.0" encoding="UTF-8"?>
<experiment>
	<optioncontainer>
		<optiongroup groupname="config">
			<option name="name" value="example1"/>
			<option name="flowchart" value="learn"/>
		</optiongroup>
		<optiongroup groupname="singlemalt">
			<option name="parsing_algorithm" value="nivrestandard"/>
		</optiongroup>
		<optiongroup groupname="input">
			<option name="infile" value="examples/data/talbanken05_train.conll"/>
		</optiongroup>
		<optiongroup groupname="nivre">
		    <option name="allow_root" value="false"/>
			<option name="allow_reduce" value="false"/>
		</optiongroup>
	</optioncontainer>
</experiment>

To run MaltParser with the above option file type:

prompt> java -jar maltparser-1.8.jar  -f examples/optionexample.xml

This command will create a configuration file example1.mco based on the settings in the option file. It is possible to override the options by
command-line options, for example:

prompt> java -jar maltparser-1.8.jar -f examples/optionexample.xml -a nivreeager

which will create a configuration based on the same setting except the parsing algorithm is now nivreeager instead of nivrestandard. If you
want to create a configuration that has the same settings as the option file with command-line options, you need to type:

prompt> java -jar maltparser-1.8.jar -c example1 -m learn
                           -i examples/data/talbanken05_train.conll -a nivrestandard
                           -ne false -nr false

To parse using one of the three configurations you simply type:

prompt> java -jar maltparser-1.8.jar -c example1 -m parse
                           -i examples/data/talbanken05_test.conll -o out1.conll

Configuration

The purpose of the configuration is to gather information about all settings and files into one file. During learning, the configuration is created and stored
in a configuration file with the file suffix .mco. This configuration file can later be reused whenever the trained model is used to parse new data.
Potentially there can be several types of configuration, but MaltParser 1.8 only knows one type: the Single Malt configuration (singlemalt).

Flow chart

MaltParser have seven pre-defined flow charts that describe what tasks MaltPasrer should perform. These seven flow charts are:

Name	Description

learn	Creates a Single Malt configuration and induces a parsing model from input data.

parse	Parses sentences using a Single Malt configuration.

info	Prints information about a configuration.

unpack	Unpacks a configuration into a directory with the same name.

proj	Creates a configuration and projectivizes input data without inducing a parsing model.

deproj	Deprojectivizes input data using a configuration.

convert	A simple data format converter

A Single Malt configuration creates a parsing model based on one set of option values. The learn and parse modes are explained above in Train a parsing model and
Parse data with your parsing model, the other four modes are described below using the same example.

Get configuration information

Sometimes it is useful to get information about a configuration, for instance, to know which settings have been used when creating the
configuration. To get this information you type:

prompt> java -jar maltparser-1.8.jar -c test -m info

This will output a lot of information about the configuration:

-----------------------------------------------------------------------------
                          MaltParser 1.8
-----------------------------------------------------------------------------
         MALT (Models and Algorithms for Language Technology) Group
             Vaxjo University and Uppsala University
                             Sweden
-----------------------------------------------------------------------------

Started: Fri May 02 23:49:37 CEST 2014
CONFIGURATION
Configuration name:   test
Configuration type:   singlemalt
Created:              Fri May 02 23:45:18 CEST 2014

SYSTEM
Operating system architecture: amd64
Operating system name:         Linux
JRE vendor name:               Oracle Corporation
JRE version number:            1.7.0_55

MALTPARSER
Version:                       1.8
Build date:                    May 2 2014

SETTINGS
2planar
  reduceonswitch (-2pr)                 false
config
  workingdir (  -w)                     user.dir
  name (  -c)                           test
  logging ( -cl)                        info
  flowchart (  -m)                      learn
  type (  -t)                           singlemalt
  logfile (-lfi)                        stdout
  url (  -u)
covington
  allow_root ( -cr)                     true
  allow_shift ( -cs)                    false
graph
  max_sentence_length (-gsl)            256
  head_rules (-ghr)
  root_label (-grl)                     ROOT
guide
  decision_settings (-gds)              T.TRANS+A.DEPREL
  kbest_type ( -kt)                     rank
  data_split_structure (  -s)
  learner (  -l)                        liblinear
  kbest (  -k)                          -1
  features (  -F)
  classitem_separator (-gcs)            ~
  data_split_column (  -d)
  data_split_threshold (  -T)           50
input
  infile (  -i)                         examples/data/talbanken05_train.conll
  reader ( -ir)                         tab
  iterations ( -it)                     1
  charset ( -ic)                        UTF-8
  reader_options (-iro)
  format ( -if)                         /appdata/dataformat/conllx.xml
lib
  save_instance_files ( -li)            false
  external ( -lx)
  verbosity ( -lv)                      silent
  options ( -lo)
multiplanar
  planar_root_handling (-prh)           normal
nivre
  allow_root ( -nr)                     true
  enforce_tree ( -nt)                   false
  allow_reduce ( -ne)                   false
output
  charset ( -oc)                        UTF-8
  writer_options (-owo)
  format ( -of)
  writer ( -ow)                         tab
  outfile (  -o)
planar
  no_covered_roots (-pcov)               false
  connectedness (-pcon)                  none
  acyclicity (-pacy)                     true
pproj
  covered_root (-pcr)                   none
  marking_strategy ( -pp)               none
  lifting_order (-plo)                  shortest
singlemalt
  parsing_algorithm (  -a)              nivreeager
  null_value ( -nv)                     one
  guide_model ( -gm)                    single
  propagation ( -fp)
  diagnostics ( -di)                    false
  use_partial_tree ( -up)               false
  diafile (-dif)                        stdout
  mode ( -sm)                           parse

DEPENDENCIES
--guide-features (  -F)                 NivreEager.xml

FEATURE MODEL
MAIN
InputColumn(FORM,Input[0])
InputColumn(FORM,Input[1])
InputColumn(FORM,Stack[0])
InputColumn(FORM,head(Stack[0]))
InputColumn(POSTAG,Input[0])
InputColumn(POSTAG,Input[1])
InputColumn(POSTAG,Input[2])
InputColumn(POSTAG,Input[3])
InputColumn(POSTAG,Stack[0])
InputColumn(POSTAG,Stack[1])
Merge(InputColumn(POSTAG,Input[0]),OutputColumn(DEPREL,ldep(Input[0])))
Merge(InputColumn(POSTAG,Stack[0]),InputColumn(POSTAG,Input[0]))
Merge(InputColumn(POSTAG,Stack[0]),OutputColumn(DEPREL,Stack[0]))
Merge3(InputColumn(POSTAG,Input[0]),InputColumn(POSTAG,Input[1]),InputColumn(POSTAG,Input[2]))
Merge3(InputColumn(POSTAG,Input[1]),InputColumn(POSTAG,Input[2]),InputColumn(POSTAG,Input[3]))
Merge3(InputColumn(POSTAG,Stack[0]),InputColumn(POSTAG,Input[0]),InputColumn(POSTAG,Input[1]))
Merge3(InputColumn(POSTAG,Stack[0]),OutputColumn(DEPREL,ldep(Stack[0])),OutputColumn(DEPREL,rdep(Stack[0])))
Merge3(InputColumn(POSTAG,Stack[1]),InputColumn(POSTAG,Stack[0]),InputColumn(POSTAG,Input[0]))
OutputColumn(DEPREL,Stack[0])
OutputColumn(DEPREL,ldep(Input[0]))
OutputColumn(DEPREL,ldep(Stack[0]))
OutputColumn(DEPREL,rdep(Stack[0]))

liblinear INTERFACE
Finished: Fri May 02 23:49:37 CEST 2014

The information is grouped into different categories:

Category	Description

CONFIGURATION	The name and type of the configuration and the date when it was created.

SYSTEM	Information about the system that was used when creating the configuration, such as processor, operating system and
version of Java Runtime Environment (JRE).

MALTPARSER	Version of MaltParser and when it was built.

SETTINGS	All option settings divided into several categories.

DEPENDENCIES	In some cases the parser self-corrects when an illegal combination of options is specified or some option is missing.
In the example above the feature specification file is not specified and the parser uses the default feature specification file for the Nivre arc-eager parsing algorithm.

FEATURE MODEL	Outputs the content of the feature specification file.

<LEARNER> INTERFACE	Information about the interface to the learner, in this case LIBSVM.

<LEARNER> SETTINGS	All settings of specific learner options, in this case LIBSVM.

Unpack a configuration

It is possible to unpack the configuration file test.mco by typing:

prompt> java -jar maltparser-1.8.jar -c test -m unpack

This command will create a new directory test containing the following files:

File	Description

conllx.xml	XML document describing the data format.

NivreEager.xml	XML document containing the feature model specification.

odm0.libsvm.moo, odm0.libsvm.map	The LIBSVM model that is used for predicting the next parsing action.

savedoptions.sop	All option settings that cannot be changed during parsing.

symboltables.sym	All distinct symbols in the training data, divided into different columns.
For example, the column POSTAG in the CoNLL format has its own symbol table with all distinct values occurring in the training data.

test_singlemalt.info	Information about the configuration (same as described above).

Projectivize input data

It is possible to projectivize an input file, with or without involving parsing.

All non-projective arcs in the input file are replaced by projective arcs by applying a lifting operation. The lifts are encoded in the
dependency labels of the lifted arcs. The encoding scheme can be varied using the flag -pp (marking_strategy), and there are
currently five of them: none, baseline, head, path and head+path. (See Nivre & Nilsson (2005) for
more details concerning the encoding schemes.) A dependency file can be projectivized using the head encoding by typing:

prompt> java -jar maltparser-1.8.jar -c pproj -m proj
                           -i examples/data/talbanken05_test.conll
                           -o projectivized.conll
                           -pp head

There is one additional option for the projectivization called covered_root, which is mainly used for handling dangling punctuation.
Depending on the treebank, a punctuation token located in the middle of a sentence can attach directly to the root, which entails that all
arcs crossing the head arc of the punctuation token are non-projective. This, in turn, results in lots of (unnecessary) lifts, and can be
avoided by using the covered_root flag -pcr. This option has four values: none, left, right and head.
For the last three values, tokens like dangling punctuation are then attached to one of the tokens connected by the shortest arc
covering the token, either the leftmost (left), rightmost (right), or head (head) token of the covering arc.
This will prevent all the unnecessary lifts.

The projecitivization and deprojectivization (below), including the encoding schemes, are know as pseudo-projective transformations and are
described in more detail in Nivre & Nilsson (2005). The only difference compared to Nivre & Nilsson is that it is the most deeply nested
non-projective arc that is lifted first, not the shortest one.

Deprojectivize output data

MaltParser can also be used to deprojectivize a projective file containing pseudo-projective encoding, with or without involving parsing,
where it is assumed that the configuration pproj contains the same encoding scheme as during projectivization. It could look like this:

prompt> java -jar maltparser-1.8.jar -c pproj -m deproj
                           -i projectivized.conll
                           -o deprojectivized.conll

The file deprojectivized.conll will contain the deprojectivized data. Note that is is only the encoding schemes head,
path and head+path that actively try to recover the non-projective arcs.

Input and output format

The format and encoding of the input and output data is controlled by the format, reader, writer and charset options
in the input and output option group. The CoNLL,
Malt-TAB and simplified version of
Negra data format specification files are already included in
the MaltParser jar-file (maltparser-1.8.jar) in the appdata/dataformat directory. The CoNLL data format specification file looks like this:

<?xml version="1.0" encoding="UTF-8"?>
<dataformat name="conllx">
	<column name="ID" category="INPUT" type="INTEGER"/>
	<column name="FORM" category="INPUT" type="STRING"/>
	<column name="LEMMA" category="INPUT" type="STRING"/>
	<column name="CPOSTAG" category="INPUT" type="STRING"/>
	<column name="POSTAG" category="INPUT" type="STRING"/>
	<column name="FEATS" category="INPUT" type="STRING"/>
	<column name="HEAD" category="HEAD" type="INTEGER"/>
	<column name="DEPREL" category="DEPENDENCY_EDGE_LABEL" type="STRING"/>
	<column name="PHEAD" category="IGNORE" type="INTEGER" default="_"/>
	<column name="PDEPREL" category="IGNORE" type="STRING" default="_"/>

</dataformat>

A data format specification file has two types of XML elements. First, there is the dataformat element with the attribute name, which
gives the data format a name. The dataformat element encloses one or more column elements, which contain information about individual columns.
The column elements have three attributes:

Attribute	Description

name	The column name. Note that the column name can be used by an option and within a feature model specification as an identifier of the column.

category	The column category, one of the following:

INPUT	Input data in both learning and parsing mode, such as part-of-speech tags or word forms.

DEPENDENCY_EDGE_LABEL	Column containing a dependency label. If the parser is to learn to produce labeled dependency graphs, these must be present in learning mode.

OUTPUT	Same as DEPENDENCY_EDGE_LABEL, used by MaltParser version 1.0-1.1

PHRASE_STRUCTURE_EDGE_LABEL	Column containing a phrase structure edge label.

PHRASE_STRUCTURE_NODE_LABEL	Column containing a phrase category label.

SECONDARY_EDGE_LABEL	Column containing a secondary edge label.

HEAD	The HEAD column defines the unlabeled structure of a dependency graph and is also output data of the parser in parsing mode.

IGNORE	The column value will be ignored and therefore will not be present in the output file.

type	Defines the data type of the column and/or its treatment during learning and parsing:

STRING	The column value will be used as a string value in the feature model.

INTEGER	The column value will be used as an integer value in the feature model.

BOOLEAN	The column value will be used as a boolean value in the feature model.

REAL	The column value will be used as a real value in the feature model.

default	The default output for columns that have the column type IGNORE.

It is possible to define your own input/output format and then supply the data format specification file with the format option.

Currently, MaltParser only supports tab-separated data files, which means that a sentence in a data file in the CoNLL
data format could look like this:

1	Den	_	PO	PO	DP	2	SS	_	_
2	blir	_	V	BV	PS	0	ROOT	_	_
3	gemensam	_	AJ	AJ	_	2	SP	_	_
4	för	_	PR	PR	_	2	OA	_	_
5	alla	_	PO	PO	TP	6	DT	_	_
6	inkomsttagare	_	N	NN	HS	4	PA	_	_
7	oavsett	_	PR	PR	_	2	AA	_	_
8	civilstånd	_	N	NN	SS	7	PA	_	_
9	.	_	P	IP	_	2	IP	_	_

Finally, the character encoding can be specified with the charset option and this option is used by MaltParser to define
the java class Charset.

Parsing Algorithm

Any deterministic parsing algorithm compatible with the MaltParser architecture can be implemented in the MaltParser package. MaltParser 1.8
contains three families of parsing algorithms: Nivre, Covington and Stack.

Nivre

Nivre's algorithm (Nivre 2003, Nivre 2004) is a linear-time algorithm limited to projective dependency structures. It can
be run in arc-eager (-a nivreeager) or arc-standard (-a nivrestandard) mode. In addition,
the allow_root option decides whether the parser will start parsing with
an artificial root token on the stack (true) or with an empty stack (false), and
the allow_reduce option decides whether the reduce transition is allowed even if the token on top
of the stack does not have a head (true) or whether only attached tokens can be reduced (false). The enforce_tree option can be used with the
arc-eager version to make sure that the output parse is a tree.

Nivre's algorithm uses two data structures:

A stack Stack of partially processed tokens, where Stack[i] is the i+1th token from the top of the stack, with the top being Stack[0].

A list Input of remaining input tokens, where Input[i] is the i+1th token in the list, with the first token being Input[0].

NB:  Please note that the allow_root and allow_reduce options replace the older root_handling option from version 1.7. In order
to replicate the behavior of older versions, use the following settings:

root_handling = normal corresponds to allow_root = true and allow_reduce = true

root_handling = relaxed corresponds to allow_root = false and allow_reduce = true

root_handling = strict corresponds to allow_root = false and allow_reduce = false

The new default behavior is allow_root = true and allow_reduce = false.

Covington

Covington's algorithm (Covington 2001) is a quadratic-time algorithm for unrestricted dependency structures, which proceeds by trying to
link each new token to each preceding token. It can be run in a projective (-a covproj) mode, where the linking operation is restricted to
projective dependency structures, or in a non-projective (-a covnonproj) mode, allowing non-projective (but acyclic) dependency structures.
In addition, there are two options, allow shift and allow root,
that controls the behavior of Covington's algorithm.

Covington's algorithm uses four data structures:

A list Left of partially processed tokens, where Left[i] is the i+1th token in the list, with the first token being Left[0].

A list Right of remaining input tokens, where Right[i] is the i+1th token in the list, with the first token being Right[0].

A list LeftContext of unattached tokens to the left of Right[0] (and to the right of Left[0]), where LeftContext[i] is the i+1th
such token, with LeftContext[0] being the token immediately to the left of Right[0].

A list RightContext of unattached tokens to the right of Left[0] (and to the left of Right[0]), where RightContext[i] is the i+1th
such token, with RightContext[0] being the token immediately to the right of Left[0].

Stack

The Stack algorithms are similar to Nivre's algorithm in that they use a stack and a buffer but differ in that they add arcs
between the two top nodes on the stack (rather than the top node on the stack and the first node in the buffer) and that they guarantee
that the output is a tree without post-processing. The Projective (-a stackproj) Stack algorithm uses essentially the same transitions
as the arc-standard version of Nivre's algorithm and is limited to projective dependency trees. The Eager (-a stackeager) and
Lazy (-a stacklazy) Stack algorithms in addition make use of a swap transition, which makes it possible to derive arbitrary
non-projective dependency trees. The Eager algorithm applies the swap transition as soon as possible, while the Lazy algorithm postpones
swapping as long as possible. The Stack algorithms are described in Nivre (2009) and Nivre, Kuhlmann and Hall (2009).

The Stack algorithms use three data structures:

A stack Stack of partially processed tokens, where Stack[i] is the i+1th token from the top of the stack, with the top being Stack[0].

A list Input, which is a prefix of the buffer containing all nodes that have been on Stack, where Input[i] is the i+1th token from the start of Input.

A list Lookahead, which is a suffix of the buffer containing all nodes that have not been on Stack, where Lookahead[i] is the i+1th token from the start of Lookahead.

Note that it is only the swap transition that can move nodes from Stack back to the buffer, which means that for the Projective Stack algorithm Input will always be empty and Lookahead will always contain all the nodes in the buffer.

Planar

The Planar algorithm (Gómez-Rodríguez and Nivre, 2010)
is a linear-time algorithm limited to planar dependency structures, the
set of structures that do not contain any crossing links. It works in a
similar way to Nivre's algorithm in arc-eager mode, but with more
fine-grained transitions. The connectedness, acyclicity and no covered roots
options can be used to configure which additional constraints, apart
from planarity, will be imposed on the target set of dependency graphs.

Just like Nivre's algorithm, the Planar algorithm uses two data structures:

A stack Stack of partially processed tokens, where Stack[i] is the i+1th token from the top of the stack, with the top being Stack[0].

A list Input of remaining input tokens, where Input[i] is the i+1th token in the list, with the first token being Input[0].

2-Planar

The 2-Planar algorithm (Gómez-Rodríguez and Nivre,
2010) is a linear-time algorithm that can be used to parse 2-planar
dependency structures, i.e., those whose links may be coloured with two
colours in such a way that no two same-coloured links cross. The
2-planar algorithm uses two stacks, one of which is the active stack at
a given time while the other is the inactive stack. Input words are
always pushed into both stacks at the same time, but then the algorithm
behaves like the Planar parser working with only one stack (the active
stack), until a Switch transition is executed: this transition switches
the stacks around, making the previously inactive stack active and vice
versa.

The reduce on switch option can be used to change the specific behaviour of Switch transitions, while the planar root handling option can be employed to change the algorithm's behavior with respect to root tokens.

The 2-Planar algorithm uses three data structures:

An active stack (ActiveStack) of partially processed tokens that may be linked on a given plane, where ActiveStack[i] is the i+1th token from the top of the stack, with the top being ActiveStack[0].

An inactive stack (InactiveStack) of partially processed tokens that may be linked on the other plane, where InactiveStack[i] is the i+1th token from the top of the stack, with the top being InactiveStack[0].

A list Input of remaining input tokens, where Input[i] is the i+1th token in the list, with the first token being Input[0].

Feature model

MaltParser uses history-based feature models for predicting the next action in the deterministic derivation of a dependency
structure, which means that it uses features of the partially built dependency structure together with features of
the (tagged) input string. Features that make use of the partially built dependency structure corresponds to the OUTPUT category of
the data format, for example DEPREL in the CoNLL data format, and features of the input string corresponds to the INPUT
category of the data format, for example CPOSTAG and FORM.

The feature model specification must be specified in an XML file according to the format below or in a text file formatted according to the specification
given by the MaltParser 0.x user guide. The latter specification format should be saved in a text file where the file name must end
with the file suffix .par.

Below you can see an example of the new XML format (Nivre arc-eager default feature model):

<?xml version="1.0" encoding="UTF-8"?>
<featuremodels>
	<featuremodel name="nivreeager">
		<feature>InputColumn(POSTAG, Stack[0])</feature>
		<feature>InputColumn(POSTAG, Input[0])</feature>
		<feature>InputColumn(POSTAG, Input[1])</feature>
		<feature>InputColumn(POSTAG, Input[2])</feature>
		<feature>InputColumn(POSTAG, Input[3])</feature>
		<feature>InputColumn(POSTAG, Stack[1])</feature>
		<feature>OutputColumn(DEPREL, Stack[0])</feature>
		<feature>OutputColumn(DEPREL, ldep(Stack[0]))</feature>
		<feature>OutputColumn(DEPREL, rdep(Stack[0]))</feature>
		<feature>OutputColumn(DEPREL, ldep(Input[0]))</feature>
		<feature>InputColumn(FORM, Stack[0])</feature>
		<feature>InputColumn(FORM, Input[0])</feature>
		<feature>InputColumn(FORM, Input[1])</feature>
		<feature>InputColumn(FORM, head(Stack[0]))</feature>
	</featuremodel>
</featuremodels>

Each feature is defined using a functional notation with three types of functions:

Type	Description

Address function	There are two types of address functions: parsing algorithm specific functions and dependency graph functions.
The parsing algorithm specific functions have the form Data-structure[i], where Data-structure is a data structure used by a specific parsing algorithm
and i is an offset from the start position in this data structure. The following data structures are available for different parsing algorithms:

Nivre arc-eager	Stack, Input

Nivre arc-standard	Stack, Input

Covington projective	Left, Right.

Covington non-projective	Left, Right, LeftContext, RightContext.

Stack projective	Stack, Input, Lookahead

Planar	Stack, Input

2-Planar	ActiveStack, InactiveStack, Input

The dependency graph address functions take a graph node as argument and navigates from this graph node to another graph node (if possible).
There are seven dependency graph address functions:

head	Returns the head of the graph node if defined; otherwise, a null-value.

ldep	Returns the leftmost (left) dependent of the graph node if defined; otherwise, a null-value.

rdep	Returns the rightmost (right) dependent of the graph node if defined; otherwise, a null-value.

lsib	Returns the next left (same-side) sibling of the graph node if defined; otherwise, a null-value.

rsib	Returns the next right (same-side) sibling of the graph node if defined; otherwise, a null-value.

pred	Returns the predecessor of the graph node in the linear order of the input string if defined; otherwise, a null-value.

succ	Returns the successor of the graph node in the linear order of the input string if defined; otherwise, a null-value.

anc	Returns the ancestor of the graph node if defined; otherwise, a null-value.

panc	Returns the proper ancestor of the graph node if defined; otherwise, a null-value.

ldesc	Returns the leftmost descendant of the graph node if defined; otherwise, a null-value

pldesc	Returns the proper leftmost descendant of the graph node if defined; otherwise, a null-value.

rdesc	Returns the rightmost descendant of the graph node if defined; otherwise, a null-value.

prdesc	Returns the proper rightmost descendant of the graph node if defined; otherwise, a null-value.

Feature function	A feature function takes at least one address function as input and returns a feature value defined in terms of the input arguments.
There are seven feature functions available:

InputColumn	Takes two arguments, a column name and an address function, and returns
the column value for the node identified by the address function.
The column name must correspond to an input column in the data format and the address function
 must return a token node in the input string. (If the address function is undefined, a null-value is returned.) Example:

InputColumn(POSTAG, Stack[0])

OutputColumn	Takes two arguments, a column name and an address function, and returns the column value for the node identified by the address function. The column name must correspond to an output column in the data format and the address function must
 return a graph node in the dependency graph. (If the address function is undefined, a null-value is returned.) Example:

OutputColumn(DEPREL, Stack[0])

InputArc	Takes three arguments, a column name and two address functions, and returns LEFT, RIGHT or NULL depending on whether the column value defines a left-pointing, right-pointing or no arc between the two nodes identified by the address functions. The column name must correspond to an input column of integer type in the data format and the address functions must return token nodes in the input string. (If one of the address functions is undefined, a null-value is returned.) This feature function can be used to define features over the dependency graph predicted by another parser and given as input to MaltParser. Example:

InputArc(PHEAD, Stack[0], Input[0])

InputArcDir	Takes two arguments, a column name and an address function, and returns LEFT, RIGHT or ROOT depending on whether the column value defines the head of the node identified by the address function to be situated on the left or on the right or to be the artificial root node. The column name must correspond to an input column of integer type in the data format and the address function must return a token node in the input string. (If the address function is undefined, a null-value is returned.) This feature function can be used to define features over the dependency graph predicted by another parser and given as input to MaltParser. Example:

InputArcDir(PHEAD, Stack[0])

InputTable	Takes two arguments, a column name and an address function, and returns the column value for the node  identified by the address function. The column name must correspond to a new column defined in a
propagation specification and the address function must return a token node in the input string. (If the address function is undefined, a null-value is returned.) Example:

InputTable(CJ-POSTAG, Stack[0])

Exists	Takes an address function as argument and returns TRUE if the address function returns an existing node (and FALSE otherwise). Example:

Exists(ldep(Stack[0]))

Distance	Takes three arguments, two address functions and a normalization string, and returns the string distance (number of intervening words) between the words identified by the address functions. The normalization string is a list of integers (separated by "|") specifying the intervals used to discretize the distance metric. The list must start with 0 and be sorted in ascending order. The value returned is (a category corresponding to) the greatest integer in the normalization string that is smaller than or equal to the exact distance. Example:

Distance(Stack[0], Input[0], 0|1|2|5)

This feature function returns the number of words occurring between the token on top of the stack and the first token in the input buffer, with discrete categories 0, 1, 2-4 and 5-.

NumOf	Takes three arguments, an address function, a relation name, and a normalization string, and returns the number of nodes having the specified relation to the node identified by the address function. Valid relation names are ldeps and rdeps and deps (for left dependent, right dependent and dependent, respectively). The normalization string is a list of integers (separated by "|") specifying the intervals used to discretize the metric. The list must start with 0 and be sorted in ascending order. The value returned is (a category corresponding to) the greatest integer in the normalization string that is smaller than or equal to the exact number. Example:

NumOf(Stack[0], ldeps, 0|1|2|5)

This feature function returns the number of left dependents of the token on top of the stack, with discrete categories 0, 1, 2-4 and 5-.

Feature map function	Maps a feature value onto a new set of values and takes as arguments a feature specification
and one or more arguments that control the mapping. There is one feature map function:

Split	Splits the feature value into a set of feature values. In addition to a feature specification it takes a
delimiter (regular expression) as an argument.
The example below shows how the value of the FEATS column in the CoNLL data format is split into a set of values using the delimiter |:

Split(InputColumn(FEATS, Input[0]),\|)

Suffix	Extract the suffix of a feature value (only InputColumn) with a suffix length n. By convention, if n = 0, the
entire feature value is included; otherwise only the n last characters are included in the feature value. The following specification defines a feature
the value of which is the four-character suffix of the word form (FORM) of the next input token.

Suffix(InputColumn(FORM, Input[0]), 4)

Prefix	Extract the prefix of a feature value with a prefix length n. By convention, if n = 0, the entire
feature value is included; otherwise only the n first characters are included in the feature value. The following specification defines a feature
the value of which is the four-character prefix of the word form (FORM) of the next input token.

Prefix(InputColumn(FORM, Input[0]), 4)

Merge	Merge two feature value into one feature value. The following specification defines a feature
the value of which the part-of-speech of the top token of the stack and the next input token are merged into one feature value.

Merge(InputColumn(POSTAG, Stack[0]), InputColumn(POSTAG, Input[0]))

Merge3	Merge three feature value into one feature value. The following specification defines a feature
the value of which the part-of-speech of the three next input token are merged into one feature value.

Merge3(InputColumn(POSTAG, Input[0]), InputColumn(POSTAG, Input[1]), InputColumn(POSTAG, Input[2]))

MaltParser is equipped with a default feature model specification for each parsing algorithm and it automatically identifies the corresponding
feature model specification. It is possible to define your own feature model specification using the description above and using
the --guide-features option to specify the feature model specification file.

Learner

MaltParser can be used with different learning algorithms to induce classifiers from training data. From version 1.3 there are two built-in learners: LIBSVM and LIBLINEAR.

LIBSVM

LIBSVM (Chang and Lin 2001) is a machine learning package for support vector machines with different kernels. Information about different options can be found on the LIBSVM web site.

LIBLINEAR

LIBLINEAR (Fan et al. 2008) is a machine learning package for linear classifiers. Information about different options can be found on the LIBLINEAR web site.

Prediction strategy

From version 1.1 of MaltParser it is possible to choose different prediction strategies. Previously, MaltParser (version 1.0.4 and earlier)
combined the prediction of the transition with the prediction of the arc label into one complex prediction with one feature model. With MaltParser 1.1
and later versions it is possible to divide the prediction of the parser action into several predictions. For example with the Nivre arc-eager algorithm,
it is possible to first predict the transition; if the transition is SHIFT or REDUCE the nondeterminism is resolved, but if the predicted transition is RIGHT-ARC
or LEFT-ARC the parser continues to predict the arc label. This prediction strategy enables the system to have three different feature models: one for predicting
the transition and two for predicting the arc label (RIGHT-ARC and LEFT-ARC).

To control the prediction strategy the --guide-decision_settings option is used with following notation:

Notation	Name	Description

T.TRANS+A.DEPREL	Combined prediction	Combines the prediction of the transition (T.TRANS) and the arc label (A.DEPREL).
This is the default setting of MaltParser 1.1 and was the only setting available for previous versions of MaltParser.

T.TRANS,A.DEPREL	Sequential prediction	First predicts the transition (T.TRANS) and
continues to predict the arc label (A.DEPREL) if the transition requires an arc label.

T.TRANS#A.DEPREL	Branching prediction	First predicts the transition (T.TRANS)
and if the transition does not require any arc label then the nondeterminism is resolved, but if the predicted transition
requires
an arc label then the parser continues to predict the arc label. If the transition is a left arc transition it predicts the arc label using the
corresonding model for left arc transition and if it is a right arc transition it uses the right arc model.

To differentiate the feature model when using sequential prediction you can specify two submodels for T.TRANS and A.DEPREL. Here is a truncated example:

<?xml version="1.0" encoding="UTF-8"?>
<featuremodels>
	<featuremodel name="sequential">
		<submodel name="T.TRANS">
			<feature>InputColumn(POSTAG, Stack[0])</feature>
			<feature>InputColumn(POSTAG, Input[0])</feature>
			<feature>InputColumn(POSTAG, Input[1])</feature>
			...
		</submodel>
		<submodel name="A.DEPREL">
			<feature>InputColumn(POSTAG, Stack[0])</feature>
			<feature>InputColumn(POSTAG, Input[0])</feature>
			<feature>InputColumn(POSTAG, Input[1])</feature>
			...
			<feature>InputColumn(FORM,ldep(Input[0]))</feature>
			<feature>InputColumn(FORM,rdep(Stack[0]))</feature>
		</submodel>
	</featuremodel>
</featuremodels>

When using branching prediction it is possible to use three submodels (T.TRANS, RA.A.DEPREL and LA.A.DEPREL), where RA denotes the right arc model and
LA the left arc model:

<?xml version="1.0" encoding="UTF-8"?>
<featuremodels>
	<featuremodel name="branched">
		<submodel name="T.TRANS">
			<feature>InputColumn(POSTAG, Stack[0])</feature>
			<feature>InputColumn(POSTAG, Input[0])</feature>
			<feature>InputColumn(POSTAG, Input[1])</feature>
			...
		</submodel>
		<submodel name="RA.A.DEPREL">
			<feature>InputColumn(POSTAG, Stack[0])</feature>
			<feature>InputColumn(POSTAG, Input[0])</feature>
			<feature>InputColumn(POSTAG, Input[1])</feature>
			...
			<feature>InputColumn(FORM,ldep(Input[0]))</feature>
			<feature>InputColumn(FORM,rdep(Stack[0]))</feature>
		</submodel>
		<submodel name="LA.A.DEPREL">
			<feature>InputColumn(POSTAG, Stack[0])</feature>
			<feature>InputColumn(POSTAG, Input[0])</feature>
			<feature>InputColumn(POSTAG, Input[1])</feature>
			...
			<feature>InputColumn(FORM,ldep(Input[0]))</feature>
			<feature>InputColumn(FORM,rdep(Stack[0]))</feature>
   		</submodel>
	</featuremodel>
</featuremodels>

If the feature specification file does not contain any submodels then the parser uses the same feature model for all submodels.

Partial trees

Since MaltParser 1.4 it is possible to parse with partial trees, i.e., sentences may be input with a partial dependency structure, a subgraph of a complete dependency tree. To parse with partial trees you need to do the following:

Add two input data columns to your data format file: PARTHEAD defines the unlabeled structure of a partial dependency tree by specifying the head of each token (and 0 if the token is a root in the partial dependency graph) and PARTDEPREL defines the dependency labels of the partial dependency tree.

Add the partial dependency structure to the columns PARTHEAD and PARTDEPREL in your input file.

The option --singlemalt-use_partial_tree need to be set to true by using the command line flag -up true

The two data columns should look like these:

	<column name="PARTHEAD" category="INPUT" type="INTEGER"/>
	<column name="PARTDEPREL" category="INPUT" type="STRING"/>

Note: To benefit from the partial dependency structure, the parser model should also be trained on partial trees. Moreover, since arcs can only be added between roots of the partial tree, the partial tree should satisfy the following constraint: if an arc (i, j) is included, then the subtree rooted at j in the complete tree must also be included.

Propagation

Since MaltParser 1.4 it is possible to propagate column values towards the root of the dependency graph when a labeled transition is performed. The propagation is managed by a propagation specification
file formatted in XML with the following attributes:

Attribute	Name	Description

FROM	The data column from which the values are copied.

TO	The data column to which the values are copied. This data column should not exist in the data format and the values are interpreted as sets. When a new value is copied to this column, the result is the set union of the new value and the old value. The atomic values (set members) are separated by the sign |.

FOR	A subset of values that can be copied (other values will not be copied). If empty then all values will be copied.

OVER	A subset of dependency labels that allow propagation when a labeled transition is performed. If empty then all dependency labels allow propagation.

Below you can see an example of a propagation specification file:

<?xml version="1.0" encoding="UTF-8"?>
<propagations>
   <propagation name="coordination">
      <from>POSTAG</from>
      <to>CJ-POSTAG</to>
      <for></for>
      <over>CJ</over>
   </propagation>
   <propagation name="valency">
      <from>DEPREL</from>
      <to>VALENCY</to>
      <for>EO|ES|FO|FS|IO|OA|OO|OP|SP|SS|VO|VS</for>
      <over></over>
   </propagation>
</propagations>

The top half specifies that POSTAG values should be copied to the CJ-POSTAG field of the head, whenever an arc with the label CJ (for conjunct) is created. Assuming an analysis of coordination where the coordinating conjunction is the head of coordinate structure, this will have the effect of propagating information about the POSTAG values of the conjuncts to the head of the coordinate structure.

The bottom half specifies that DEPREL values should be copied to the VALENCY field of the head, whenever an arc labeled by one of the labels listed in the FOR parameter is created. Provided that these labels denote valency-bound functions, this will have the effect of propagating information about satisfaction of valency constraints to the head.

New columns introduced in the FROM attribute of a propagation specification can be referenced in feature specifications using the function InputTable, e.g. <feature>InputTable(CJ-POSTAG, Stack[0])</feature>.

Phrase structure parsing

MaltParser 1.1 and MaltParser 1.2 can be turned into a phrase structure parser that recovers both continuous and discontinuous
phrases with both phrase labels and grammatical functions. The parser induces a parser model from treebank data by automatically
transforming the phrase structure representations into dependency representations with complex arc labels,
which makes it possible to recover the phrase structure with both phrase labels and grammatical functions
(See Hall (2008), Hall and Nivre (2008a) and Hall and Nivre (2008b) for more details).

Note: The implementation of phrase structure parsing has been removed in later releases of MaltParser. Please
download MaltParser 1.2 and read the offline user guide of this version to parse phrase structure with MaltParser 1.2.

MaltParser API

From version MaltParser-1.8 there is a new interface to MaltParser located in org.maltparser.concurrent and contains following classes:

org.maltparser.concurrent.ConcurrentMaltParserModel

org.maltparser.concurrent.ConcurrentMaltParserService

org.maltparser.concurrent.ConcurrentUtils

This interface can only be used during parsing time and can hopefully be used in a multi-threaded environment. If you need an interface to MaltParser
during training of parser models then you have to use the old interface (see below).

The concurrent interface uses a more "light-weighted" parser and hopefully supports almost all features. One know exception is feature propagation is not supported
in the new "light-weighted" parser.

To compile the examples in srcex/org/maltparser/examples

cd examples/apiexamples
javac -d classes -cp ../../maltparser-1.8.jar:. srcex/org/maltparser/examples/*.java

To run the examples you first need to create a Swedish parser model swemalt-mini.mco by using MaltParser:

java -jar ../../maltparser-1.8.jar -w output -c swemalt-mini -i ../data/swemalt-mini/gold/sv-stb-dep-mini-train.conll -a stacklazy -m learn \
-l liblinear -llo -s_4_-c_0.1 -d CPOSTAG -s Stack[0] -T 1000 -F ../data/swemalt-mini/swedish-swap.xml

Note that swemalt-mini.mco is not the same as swemalt.mco you find on http://www.maltparser.org. swemalt-mini.mco is trained on approximately 5% of
the training data and will not perform as well as the pre-trained model find on http://www.maltparser.org.

java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.ParseSentence1
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.ParseSentence2
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.ParseSentence3
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.ConcurrentExample1
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.ConcurrentExample2
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.ConcurrentExample3

Old MaltParserService interface

Before MaltParser-1.8 there was another interface to MaltParser. Note that this interface can only be used in a single-threaded environment
and the interface doesn't use the light-weighted parser.

There are two ways to call the MaltParserService:

By running experiments, which allows other programs to train a parser model or parse with a parser model. IO-handling is done by MaltParser.

By first initializing a parser model and then calling the method parse() for each sentence that should be parsed by MaltParser. IO-handling of the sentence is then done by the third-party program.

For more information about how to use MaltParserService, please see the examples provided in the directory examples/apiexamples/srcex/org/maltparser/examples/old

To compile the old examples (srcex/org/maltparser/examples/old) used by MaltParser-1.7.2 and previous versions of MaltParser

javac -d classes -cp ../../maltparser-1.8.jar:. srcex/org/maltparser/examples/old/*.java

To run the old examples

java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.old.ReadWriteCoNLL ../data/talbanken05_test.conll out.conll ../../appdata/dataformat/conllx.xml UTF-8
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.old.CreateDependencyGraph
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.old.CreatePhraseStructureGraph
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.old.TrainingExperiment
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.old.ParsingExperiment
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.old.ParseSentence1
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.old.ParseSentence2
java -cp classes:../../maltparser-1.8.jar org.maltparser.examples.old.ParseSentence3

Other programs can invoke Maltparser in various ways, but the easiest way is to use the org.maltparser.MaltParserService class.

Maven repository

Since version 1.7, MaltParser is also available via the official Maven repository.

<dependency>
	<groupId>org.maltparser</groupId>
	<artifactId>maltparser</artifactId>
	<version>1.8</version>
</dependency>

MaltParser optimization

MaltParser is a fairly complex system with many parameters that need to be optimized. Simply using the system <q>out of the box</q>with default
settings is therefore likely to result in suboptimal performance.

Please read "A Quick Guide to MaltParser Optimization" to get hints and tips to
how you can optimize MaltParser.

References

Chang, C.-C. and Lin, C.-J. (2001) LIBSVM : a library for support vector machines. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.

Fan, R.-E., Chang, K.-W., Hsieh, C.-J., Wang, X.-R. and Lin, C.-J. (2008) LIBLINEAR: A library for large linear classification. Journal of Machine Learning Research 9, 1871-1874.

Hall, J. (2008) Transition-Based Natural Language Parsing with Dependency and Constituency Representations. Acta Wexionensia,
No 152/2008, Computer Science, Växjö University (PhD Thesis)

Hall, J. and J. Nivre (2008a) A Dependency-Driven Parser for German Dependency and Constituency Representations.
In Proceedings of the ACL Workshop on Parsing German (PaGe08), June 20, 2008, Columbus, Ohio, US, pp. x-x. (to appear)

Hall, J. and J. Nivre (2008b) Parsing Discontinuous Phrase Structure with Grammatical Functions.
In Ranta, A. and Nordstöm, B. (eds.) In Proceedings of the 6th International Conference on Natural Language Processing (GoTAL 2008),
LNAI 5221, Springer-Verlag, August 25-27, 2008, Gothenburg, Sweden, pp. 169-180.

Nivre, J. (2009) Non-Projective Dependency Parsing in Expected Linear Time. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, 351-359.

Nivre, J., Kuhlmann, M. and Hall, J. (2009) An Improved Oracle for Dependency Parsing with Online Reordering. In Proceedings of the 11th International Conference on Parsing
Technologies (IWPT'09).

Nivre, J. and J. Nilsson (2005) Pseudo-Projective Dependency Parsing. In Proceedings of the 43rd Annual Meeting
of the Association for Computational Linguistics, pp. 99-106.

Copyright © Johan Hall, Jens Nilsson and Joakim Nivre

redpajama_set_name: RedPajamaGithub


The first day of Spring has come and gone. This year is just flying by! Earth day is coming up and we have some tips for you on how to get that Spring Cleaning out of the way all while giving back!
Your probably thinking where do I start? Well if your car does not fit in your garage, I would say it is safe to start in there. We tend to just throw unwanted or old items in our garage and think we will just deal with them later and then we forget about them. Well now is your chance to clear it out.
First think you want to do is start with three boxes, one for things you want to keep, things you want donate and one for trash. This will make it so much easier to stay organized.
Go through your closets and then head over to the kids closets and get rid of the things that do not fit them anymore. There are so many charities you can donate gently worn clothes to. Someone gets a new outfit and you get more room in your closet, it is a win win for everyone.
Get your kids in on it and give them a box and let them go through their room and pick out toys that have outgrown and no longer interest them. Let them know they will be going to another little boy or girl who can enjoy them.
Book shelf overflowing? Still holding onto books from high school. Now is the time to clean that shelf off and wipe the dust away. Go through your old books that you have 3 times and donate them so someone else can get lost in the story.
Bathroom closets overflowing with old towels and sheets, time to make room for the new. There are a number of places to donate old towels and blankets, for example animal shelters are always in need of old towels and blankets for the animals. Or you could turn your old towels into rags and use them to clean.
There are so many ways to reuse the things in your home and give it a new purpose.
Last but not least, have a home office or office space that needs sprucing up.
Start with going through your old files and shred anything you might not need anymore.
If you need help spring cleaning your office. Give us a call at TBCC 858-689-8966 or visit at The Business Cleaning Company for a free quote and let us do the hard work for you!


Saint Hyacinth, a Saint Discarded, but oh so Necessary!!
Sadly, the Modernists who decided that Saint Hyacinth wasn't for the calendar anymore...bad decision! He was one of St Dominic's spiritual sons who was a timeless Saint for evangelization... but then THEY knew that and so...remove him from the calendar but the Traditional Latin Mass calendar makes sure he is celebrated.
Big mistake that the Modernist cabal figured the Latin Mass would never resurface.
St. Hyacinth, a great ornament of the celebrated Order of Preachers, was born in Poland. He was the son of illustrious parents, who educated him according to the dictates of Christianity. During the years devoted to his studies, he was an example of innocence, piety and industry. His uncle, the bishop of Cracow, appointed him canon in his cathedral, so that he might employ him in the administration of his See. When he left for Rome, on account of troubles at home, he took Hyacinth with him. St. Dominic, so celebrated for his apostolic zeal, and for the miracles he wrought, was there at the time. Hyacinth, observing the wonderful zeal and piety of this holy man and of his companions, felt a growing desire to join them. He and three of his fellow-travelers, who had the same inclination, went to St. Dominic and begged him to receive them into his newly founded Order. The Saint received them willingly, and instructed them how to lead a religious life, to preach in a Christian spirit, and to labor successfully for the spiritual welfare of men. After a few months, the holy founder had so thoroughly imbued them with his spirit, that he did not hesitate, after they had taken their vows, to send them into their native country, to preach the word of God and promote the salvation of souls.
At Cracow, where St. Hyacinth had formerly preached by his edifying life, he now began to preach with words, and God gave them such power, that he reformed the most hardened sinners, induced others to become more zealous in the service of the Almighty, and animated all to be more solicitous for the salvation of their souls. That all this might have a more solid foundation, he gathered a number of spiritual co-operators about him, and having instructed them according to the maxims of St. Dominic, he established a Dominican monastery at Cracow. Hyacinth, who had been chosen superior by the new members, was an example to all. Besides the prescribed fast-days of his Order, he fasted all Fridays and vigils on bread and water. The greater part of the night he passed in fervent prayer, before the Blessed Sacrament. He allowed himself only a very short rest on the bare floor, and scourged himself severely every night. The whole day was occupied with hearing confessions, preaching, visiting the sick, and similar pious exercises.
He had particular devotion to the Blessed Sacrament and to the Blessed Virgin, and never undertook anything before offering his work to God and begging the assistance of His Blessed Mother. She appeared to him once, on the eve of the feast of her Assumption, saying to him: "Be assured, my son, that thou shalt receive everything thou askest from my Son." The comfort these words afforded the holy man may be easily imagined. He, however, asked only for what was necessary for the salvation of souls. His own and his companion's pious labors were all directed to the same end. When he thought that he had firmly established religious principles and practices among the inhabitants of Cracow and the whole diocese, he sent his preachers to different places to labor in the same manner. He himself also left Cracow, and it is astonishing how many countries he journeyed through, how many convents he established everywhere: for apostolic laborers, how many souls he converted to the true faith or to a more virtuous life.
To aid his pious endeavors, God gave him power to work miracles, and so great was their number, that he might well be called the Thaumaturgus, or wonder-worker of his age. A miraculous event occurred in Russia, when the Tartars stormed Kiow, where the Saint had founded a church and convent. He was standing at the altar when they entered the city, spreading destruction and desolation around them. After finishing the Holy Sacrifice, the Saint, still in his priestly robes, took the Ciborium containing the Blessed Sacrament, and telling his priests to follow him without fear, he went towards the church door. When passing a large alabaster statue of the Blessed Virgin, before which he had often said his prayers, he distinctly heard a voice saying: "My son Hyacinth, wilt thou leave me here to be at the mercy of my enemies?" The Saint's eyes filled with tears. "How can I carry thee? " said he; "the burden is too heavy." "Only try," was the response; "my son will assist you to carry me without difficulty." The holy man with streaming eyes, took the statue and found it so light, that he could carry it with one hand. Thus, carrying the Ciborium in one hand and the statue in the other, he and his companions passed through the enemy unassailed, to the gates of the city. Not finding any soldiers there, they passed on and reached Cracow in safety.
Whether Almighty God made His servants invisible to the Tartars on this occasion, or in some other manner prevented them from harming them, is not known; but it is a fact that they left the city unmolested. When they reached the river over which there was no bridge, nor a boat to convey them across, the Saint, trusting in the power of Him Whom he carried in his right hand, and in the intercession of her whom he held in his left, fearlessly stepped upon the water, and crossed it with dry feet. A similar, and perhaps still greater miracle happened at another time. He was going to Vicegrad to preach, but, on reaching the river, found no vessel which he could use to reach the opposite bank. Spreading his cloak on the water, he sat upon it, and was floated safely across and brought his companions over in the same manner. By this and many other miracles, God glorified His servant even on earth.
For forty years this holy man had labored for the salvation of souls, when, in 1257, it was revealed to him that he should assist, in Heaven, at the triumph of the Blessed Virgin, on the feast of her glorious Assumption. On the feast of St. Mary ad Nives, he was taken sick. On the eve of the Assumption he gave his last instruction to the priests of his Order; after which he prepared for the festival, and, having recited the office of the day, he fixed his eyes on heaven, and said the psalm, "In thee, O Lord, have I hoped," to the words, "Into thy hands I commend my spirit," when he calmly expired, at the age of 74. The innocence and chastity which he possessed at the time of his baptism, remained unspotted until the end. After his death, the miracles which the Almighty continued to work through this Saint, were the means of proclaiming to all the world, the sanctity and merits of His blessed servant.
I. St. Hyacinth, carrying the Saviour of the world in one hand, and in the other, the statue of the Blessed Virgin, walked past his enemies through the city. Happy are they who carry Jesus and Mary, not only on their lips, but also in their hands! They will ever walk safely amid dangers, unharmed by the enemies of their salvation. Some carry Mary alone on their lips, not Jesus; they make some show of being devout to the Blessed Virgin, by saying certain prayers; but they offend Jesus, the Divine Son of Mary, most grievously, flattering themselves that, by their devotion to the Blessed Virgin, they are secure against the fire of hell. This is a terrible deceit of Satan. Such devotion is no devotion to the Divine Mother; as, to be devout to her, it is required, above all things, to do nothing which is displeasing to her, but to do all that is agreeable in her sight. As, then, neglect of her Divine Son, Whom she loves above all, must be displeasing to her, how can anyone hope for salvation when his whole devotion consists in a few prayers or pious acts? One who does this, divides Jesus from Mary. You must carry Jesus and Mary at the same time, and not only in your mouth, but also in your hands. You must show, by your works, that you love both with your whole heart. If you love Jesus, see that you do not offend Him; if you love Mary, arouse not the wrath of Him Whom she loves above all things. Such devotion will shield you against all dangers to your salvation, and lead you to everlasting peace and rest.
2. For forty years St. Hyacinth was devoted solely to the glory of God and the salvation of souls. He has now enjoyed, for more than five hundred years, the heavenly joys in recompense for his labors, and he will enjoy them for all eternity, O! how richly God rewards the services of His elect! "If, for one hundred years of service, He bestowed one hour of Heavenly bliss, the reward would be great," says St. Chrysostom. How grateful should we be, when, as the true faith teaches us, He promises us an eternal reward in Heaven for such short service! Who would not serve, with pleasure, so bountiful a Master? How blind and foolish are those who prefer to serve Satan! Does Satan reward his servants more liberally than God? Ask the reprobate; they will tell you. Listen to what the Almighty said, in times long past, of the difference that will, one day, be between His servants and those of Satan, and then resolve which you will serve; "Behold!" says He, "my servants shall eat, and you shall be hungry; behold, my servants shall drink, and you shall be thirsty. Behold, my servants shall rejoice, and you shall be confounded; behold, my servants shall praise for joyfulness of heart, and you shall cry for sorrow of heart, and shall howl for grief of spirit (Isaias, lxv)." What else does this mean but: "My servants shall be eternally happy in Heaven, but you shall be eternally unhappy in hell."
One of the loveliest lilies from the Dominican field today unfurls its petals at the foot of Mary's throne. Hyacinth represents on the sacred cycle that intrepid band of missionaries who, in the thirteenth and fourteenth centuries, faced the barbarism of the Tartars and Mussulmans which was threatening the West. From the Alps to the Northern frontiers of the Chinese Empire, from the islands of the Archipelago to the Arctic regions, he propagated his Order and spread the kingdom of God. On the Steppes, where the schism of Constantinople disputed its conquests with the idolatrous invaders from the North, he was seen for forty years working prodigies, confounding heresy, dispelling the darkness of infidelity.
Great was thy privilege, O son of Dominic, to be so closely associated to Mary as to enter into thy glory on the very feast of her triumph. As thou occupiest so fair a place in the procession accompanying her to heaven, tell us of her greatness, her beauty, her love for us poor creatures, whom she desires to make sharers, like thee, in her bliss.
It is through her thou wert so powerful in this thy exile, before being near her in happiness and glory. Long after Adalbert and Anscharius, Cyril and Methodius, thou didst traverse once more the ungrateful North, where thorns and briars so quickly spring up again, where the people, whom the Church has with such labour delivered from the yoke of paganism, are continually letting themselves be caught in the meshes of schism and the snares of heresy. In his chosen domain, the prince of darkness suffered fresh defeats, an immense multitude broke his chains, and the light of salvation shone further than any of thy predecessors had carried it. Poland, definitively won to the Church, became her rampart, until the days of treason which put an end to Christian Europe.
Almost innumerable miracles were worked at his tomb, including the raising of as many as fifty persons from the dead. He was canonized A.D. 1594 by Clement VIII., and Urban VIII. extended the celebration of his festival to the universal Church.
O God, who didst make Blessed Hyacinth, Thy Confessor, glorious amongst the people of divers nations for the holiness of his life and the glory of his miracles, grant that by his example we may amend our lives, and be defended by his help in all adversities. Through Christ our Lord. Amen.
Was the Homo Lobby active at World Youth Day? Just what was Homosexualist Bishop Galantino saying about Sodom?
I have been reflecting for a while as to why Catholic churchmen are doing such a bad job at promoting and defending the sanctity of Holy Matrimony. Again and again, I keep coming back to my belief that it is because the vast majority are homosexuals themselves, if not practicing homosexuals. Fr. Dariusz Oko has written and spoken of the homo lobby that is the 'dark side' of the Church.
It goes without saying that a homosexual is not too interested in defending - let along promoting - the sanctity of marriage. So what do sodomite churchmen do to continue the facade? Simple, a nominal support on paper of Holy Matrimony, but no real effort to defend, promote, encourage, teach the truth about the Sacrament of Holy Matrimony.
Fr. Z reports on the very disturbing case of an Italian Bishop Nunzio Galantino regarding his strange presentation on the biblical account of Sodom and Gomorrah.
So, what's his game here? Is it to put into the empty heads of these young people that God did NOT destroy Sodom and Gomorrah (i.e., rewrite the Bible) because He does not abominate the "sin of Sodom"?
Sure, Bp. Galantino underscores Abraham's intervention. Fine. It's great to underscore what Abraham tried to do, but NOT at the expense of the truth about what happened to Sodom and Gomorrah! As good and as positive as Abraham was, it didn't work, except for poor Lot. Moreover, when Abraham asked God to spare the cities because there might be good people in them, he is in no way condoning what the evil people did! Abraham seems to be fine with destruction of the wicked. He doesn't want the innocent to be destroyed because of and together with the wicked.
The fact that such a thing might take place at a World Youth Day is dreadful. Also, I think it is a stinging condemnation of the catechetical and biblical preparation of young people today, that anyone would think that he could get away with this.
Is it any wonder that homosexuality, bisexuality, pansexualism is spreading? How could it not be, with, for example, the "Theology of the Body" (TOB) crowd promoting, excusing deviant sexual acts between husband and wife, and this under episcopal endorsement?


text:
Independent Movies
If you love good indie movies, we've got you covered. Enjoy our selection of independent films full of unexpected characters and thoughtful stories. Leave it to us to provide all the most creative and unique indie films that will re-inspire your love of movies.
Gloria (Anne Hathaway) is an out-of-work party girl who, after getting kicked out of her apartment by her boyfriend (Dan Stevens), is forced to leave her life in New York and move back to her hometown where she's reunited with her childhood friend (Jason Sudeikis). When news reports surface that a giant creature is destroying Seoul, South Korea, Gloria gradually comes to the realization that she is somehow connected to this far-off phenomenon. As events begin to spin out of control, Gloria must...
Abigail Clayton (Selma Blair) lives alone. Very alone. In fact, the heiress has not left her Manhattan apartment for almost two decades. When the death of her elderly neighbor prompts NYPD Homicide Detective Frank Giardello (Giovanni Ribisi) to launch an investigation, the agoraphobic Abigail is distressed to find him outside her door, questioning her. Having tried to acquire the now vacant apartment to ensure her privacy, Abigail is further upset when new tenants Lillian (Amy Smart) and...
Desperate for a friend, Oliver (Azhy Robertson), a lonely young boy who feels different from everyone else, seeks solace and refuge in his ever-present cell phone and tablet. When a mysterious creature uses Oliver's devices against him to break into our world, Oliver's parents (Gillian Jacobs and John Gallagher Jr.) must fight to save their son from the monster beyond the screen.
Why do bad things happen to good people? Courteney Cox (TV's "Friends"; Scream 1, 2 & 3), Aidan Quinn (Michael Collins, Legends of the Fall) and Anthony LaPaglia (TV's "Without A Trace"; The Salton Sea) star in this dark, romantic comedy from Executive Producer Ivan Reitman about a decent man who dares to ask, "Why me?" Seth Warner (Quinn) has lost everything in his life that he holds dear - his wife, his job and his home. All of which, he suspects, is neither accident nor coincidence. He...
Conor McGregor: Notorious
Conor McGregor is the biggest star in the history of Mixed Martial Arts. Filmed over the course of 4 years, Notorious is the exclusive, all access account of Conor's meteoric rise from claiming benefits and living in his parents' spare room in Dublin to claiming multiple championship UFC belts and seven figure pay-packets in Las Vegas. Featuring unprecedented access, never before seen moments and explosive fight footage, this is the ultimate behind-the-scenes look at a sporting icon and his...
The Constant Gardener
Nominated for four Academy Awards®, The Constant Gardener stars Ralph Fiennes and Academy Award® winner for Best Supporting Actress Rachel Weisz. In this gripping suspense-thriller, a diplomat on the hunt for his wife's murderer uncovers a treacherous conspiracy that will destroy millions of innocent people - unless he can reveal its sinister roots. From the best-selling spy novel by John le Carre comes this edge-of-your-seat story of murder, deception and revenge that critics are calling "a...
A pair of ten-year-olds find an abandoned cop car in a field. When they take it for a joyride, it seems like they could kill themselves at any moment. But things only get worse when the small town sheriff goes looking for his missing car. The kids find themselves in the center of a deadly game of cat and mouse they don't understand and the only way out is to go as fast as their cop car can take them.
Screaming through the Nevada desert in a bullet-ridden Crown Vic, wily con artist Teddy Murretto (Frank Grillo) hatches a desperate plan to hide out from lethal hitman Bob Viddick (Gerard Butler): He sucker-punches rookie officer Valerie Young (Alexis Louder) to get himself arrested and locked up in a small-town police station. But jail can't protect Murretto for long. Viddick schemes his own way into detention, biding his time in a nearby cell until he can complete his mission. When the...
Make yourself at home with the Carmichael family as they experience one very special summer in their Brooklyn neighborhood that they've affectionately nicknamed "Crooklyn". Renowned director Spike Lee fashions a bold, flavorful picture of family life that People Magazine calls his "most affectionate work." Academy Award® nominee Alfre Woodard stars as Carolyn, a loving, but fiercely independent mother who along with her musician husband (Delroy Lindo) struggles to raise her family in difficult...
The tension and terror that is present-day South Africa is powerfully portrayed in director Richard Attenborough's sweeping story of black activist Stephen Biko (Denzel Washington) and a liberal white newspaper editor who risks his own life to bring Biko's message to the world. After learning of apartheid's true horrors through Biko's eyes, editor Donald Woods (Kevin Kline) discovers that his friend has been silenced by the police. Determined not to let Biko's message go unheard, Woods...
Cry-Baby
Eisenhower is President. Rock 'n' Roll is king. And Wade "Cry-Baby" Walker is the baddest hood in his high school. Johnny Depp heads up a supercool cast as the irresistible bad boy whose amazing ability to shed one single tear drives all the girls wild - especially Allison Vernon Williams (Amy Locane), a rich, beautiful "square" who finds herself uncontrollably drawn to the dreamy juvenile delinquent and his forbidden world of rockabilly music, fast cars and faster women. It's the hysterical...
Julianne Hough (Safe Haven) stars in this horror-thriller as a young bride-to-be who deliberately crashes her car off a deserted highway in an attempt to escape from a charming, predatory hitchhiker, played by Teddy Sears (Masters of Sex). When the plan backfires, trapping her in an overturned vehicle, she defends herself against a terrorizing psychopath—only to uncover a shocking truth that fuels her fight for survival.
Matthew McConaughey gives the performance of his career in this uplifting and powerful film inspired by true events. Texas cowboy Ron Woodroof (McConaughey) sees his free-wheeling life overturned when he's diagnosed as HIV-positive and given 30 days to live. Determined to survive, Woodroof decides to take matters in his own hands by tracking down alternative treatments from all over the world by means both legal and illegal. After finding an unlikely ally in Rayon (Jared Leto), he establishes a...
A Dangerous Woman
Debra Winger gives a chilling, award-worthy performance in this haunting drama of a woman nobody notices until it's too late. Martha (Winger) is an awkward, emotionally fragile woman who lives a quiet life in the guesthouse next to her Aunt Frances (Barbara Hershey). Unable to lie, she exists along the fringe of society and is used to the taunts that follow her wherever she goes. But when an alcoholic handyman (Gabriel Byrne) begins work on Frances's property, both women become intrigued by his...
Academy Award® winner Eddie Redmayne (The Theory of Everything) and Alicia Vikander (Ex Machina) star in this remarkable love story inspired by true events from Oscar®-winning director Tom Hooper (The King 's Speech). When Gerda (Vikander) asks her husband Einar Wegener (Redmayne) to fill in as a portrait model, Einar discovers the person she's meant to be and begins living her life as Lili Elbe. Having realized her true self and with Gerda's love and support, Lili embarks on a groundbreaking...
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