مقاله


کد مقاله : 139511012331304677

عنوان مقاله : Coreference Resolution Using Verbs Knowledge

نشریه شماره : 18 Spring 2017

مشاهده شده : 47

فایل های مقاله :


نویسندگان

  نام و نام خانوادگی پست الکترونیک مرتبه علمی مدرک تحصیلی مسئول
1 hasan zafari hasan_zafari@yahoo.com Teacher Assistant PhD
2 Maryam Hourali mhourali@mut.ac.ir Assistant Professor PhD
3 Heshaam Faili faili@ut.ac.ir Associate Professor PhD

چکیده مقاله

Coreference resolution is the problem of determining which mention in a text refer to the same entities, and is a crucial and difficult step in every natural language processing task. Despite the efforts that have been made in the past to solve this problem, its performance still does not meet today’s applications requirements. Given the importance of the verbs in sentences, in this work we tried to incorporate three types of their information on coreference resolution problem, namely, selectional restriction of verbs on their arguments, semantic relation between verb pairs, and the truth that arguments of a verb cannot be coreferent of each other. As a needed resource for supporting our model, we generate a repository of semantic relations between verb pairs automatically using Distributional Memory (DM), a state-of-the-art framework for distributional semantics. This resource consists of pairs of verbs associated with their probable arguments, their role mapping, and significance scores based on our measures. Our proposed model for coreference resolution encodes verbs’ knowledge with Markov logic network rules on top of deterministic Stanford coreference resolution system. Experiment results show that this semantic layer can improve the recall of the Stanford system while preserves its precision and improves it slightly.