Recall
0.84±0.00
0.83±0.01
0.26±0.02
0.82±0.01
0.58±0.02
0.82±0.01

F1-score
0.84±0.00
0.83±0.01
0.35±0.02
0.83±0.00
0.61±0.01
0.83±0.02

CoNLL es
CoNLL nl
WNUT2017
Archeology

AnEM

OntoNotes

Table 8: Comparison between MultiHashEmbed with adjusted number of
rows and
MultiEmbed using pretrained embeddings distributed by spaCy. Results are reported on the test
set. Adjusted rows for MultiHashEmbed.

MultiHashEmbed

MultiEmbed

Precision
0.77±0.01
0.75±0.01
0.27±0.03
0.83±0.01
0.60±0.01
0.82±0.01

Recall
0.77±0.01
0.72±0.01
0.12±0.02
0.81±0.00
0.49±0.01
0.79±0.01

F1-score
0.77±0.00
0.73±0.01
0.17±0.02
0.82±0.00
0.54±0.01
0.81±0.02

Precision
0.77±0.01
0.77±0.00
0.29±0.00
0.82±0.00
0.56±0.02
0.81±0.02

Recall
0.77±0.01
0.74±0.01
0.14±0.01
0.78±0.01
0.36±0.03
0.81±0.01

F1-score
0.77±0.01
0.75±0.00
0.19±0.01
0.80±0.00
0.44±0.01
0.81±0.01

CoNLL es
CoNLL nl
WNUT2017
Archeology

AnEM

OntoNotes
MULTI HASH EMBEDDINGS IN SPACY