From POS tagging to dependency parsing for biomedical event extraction
Table 10: UAS and LAS (F1) scores of re-trained models on the pre-segmented BioNLP-2009 development sentences which contain event interactions. Scores are computed on all tokens using the evaluation script from the CoNLL 2017 shared task [31].
['Metric', 'Biaffine', 'jPTDP', 'NLP4J', 'NNdep']
the intrinsic UAS and LAS (F1) scores on the pre-processed segmented BioNLP 2009 development sentences (i.e. scores with respect to predicted segmentation), for which these sentences contain event interactions. Although gold event annotations in the BioNLP 2009 test set are not available to public, it is likely that we would obtain the similar intrinsic UAS and LAS scores on the pre-processed segmented test sentences containing event interactions. This is logical because the BioNLP 2009 shared task dataset was a subset of the GENIA corpus. Among the four dependency parsers trained on GENIA, Stanford-Biaffine, jPTDP and NLP4J-dep produce similar event extraction scores on the development set, while on the the test set jPTDP and NLP4J-dep obtain the lowest and highest scores, respectively.