Anaphora Resolution of Noun Phrase Based on SVM
Qiaoming Zhu · Jisuanji gongcheng · 2009
This paper proposes an anaphora resolution of noun phrases based on Support Vector Machine(SVM). Evaluation on the MUC-6 corpus using several widely used features shows that the system achieves the F-measure of 68.6% and outperforms other similar systems. Further analysis shows that appositive,name alias and full string matching contributes most for anaphora resolution. It also shows that the distance between the antecedent candidate and the anaphor is very useful in constraining the instance generation,although including it as a feature does not help for anaphora resolution.