From POS tagging to dependency parsing for biomedical event extraction
Table 7: LAS by the CoNLL 2008 dependency labels on CRAFT.
['Type', 'Biaffine', 'jPTDP', 'NLP4J', 'NNdep', 'Avg.']
In most cases, Stanford-Biaffine obtains the highest score for each relation type on both corpora with the following exceptions: on GENIA, jPTDP gets the highest results to aux, dep and nn (as well as nsubjpass), while NLP4J-dep and NNdep obtain the highest scores for auxpass and num, respectively. On GENIA the labels associated with the highest average LAS scores (generally >90%) are amod, aux, auxpass, det, dobj, mark, nsubj, nsubjpass, pobj and root whereas on CRAFT they are NMOD, OBJ, PMOD, PRD, ROOT, SBJ, SUB and VC. These labels either correspond to short dependencies (e.g. aux, auxpass and VC), have strong lexical indications (e.g. det, pobj and PMOD), or occur very often (e.g. amod, subj, NMOD and SBJ). Stanford-Biaffine achieves the highest scores on all these tags except TO where the traditional feature-based model NLP4J-dep obtains the highest score Among listed tags VBG is the least and second least frequent one in GENIA and CRAFT, respectively, and generally associates to longer dependency distances. So, it is reasonable that the lowest scores we obtain on both corpora are accounted for by VBG. The coordinating conjunction tag CC also often corresponds to long dependencies, thus resulting in biggest ranges across parsers on both GENIA and CRAFT.