Minimalistic Approach to Coreference Resolution in Lithuanian Medical Records

Table 1

Comparison of coreference resolution approaches.

Method	Foundation	Precision	Recall	F1
Hobbs [32]	Syntactic tree with labeled nodes, syntactic rules, selection constraint rules	0.81–0.91	na	na
BFP [33]	Centering theory	0.49–0.90	na	na
Left-right centering [34]	Modified centering theory	0.72–0.81	na	na
Mitkov [35]	POS tagger, antecedent indicators	0.897	na	na
RAP [36]	Salience factors	0.85–0.89	na	na
Xrenner [37]	Syntactic and semantic rules	0.51–0.55	0.49–0.57	0.49–0.56
Probabilistic [38]	Bayesian rule	0.82–0.84	na	na
MARS [39]	Genetic algorithms	0.53–0.84	na	na
Soon et al. [40]	Machine learning (decision tree C5)	0.65–0.69	0.53–0.56	0.62
ILP [41]	Machine learning (logistic classifier)	0.78–0.89	0.47–0.58	0.61–0.68
Wiseman et al. [42]	Deep learning	0.77	0.70	0.73
Lee et al. [43]	Deep learning	0.81	0.73	0.77
Žitnik et al. [44]	Conditional random fields	0.68–0.94	0.30–0.87	0.41–0.87