Mining Wikipedia for Large-Scale Repositories of Context-Sensitive Entailment Rules
Authors | Milen Kouylekov Yashar Mehdad Matteo Negri |
|---|---|
Publication date | 2010 |
Links | Original |
Mining Wikipedia for Large-Scale Repositories of Context-Sensitive Entailment Rules - scientific work related to Wikipedia quality published in 2010, written by Milen Kouylekov, Yashar Mehdad and Matteo Negri.
Overview
This paper focuses on the central role played by lexical information in the task of Recognizing Textual Entailment. In particular, the usefulness of lexical knowledge extracted from several widely used static resources, represented in the form of entailment rules, is compared with a method to extract lexical information from Wikipedia as a dynamic knowledge resource. The proposed acquisition method aims at maximizing two key features of the resulting entailment rules: coverage (i.e. the proportion of rules successfully applied over a dataset of TE pairs), and context sensitivity (i.e. the proportion of rules applied in appropriate contexts). Evaluation results show that Wikipedia can be effectively used as a source of lexical entailment rules, featuring both higher coverage and context sensitivity with respect to other resources.
Embed
Wikipedia Quality
Kouylekov, Milen; Mehdad, Yashar; Negri, Matteo. (2010). "[[Mining Wikipedia for Large-Scale Repositories of Context-Sensitive Entailment Rules]]".
English Wikipedia
{{cite journal |last1=Kouylekov |first1=Milen |last2=Mehdad |first2=Yashar |last3=Negri |first3=Matteo |title=Mining Wikipedia for Large-Scale Repositories of Context-Sensitive Entailment Rules |date=2010 |url=https://wikipediaquality.com/wiki/Mining_Wikipedia_for_Large-Scale_Repositories_of_Context-Sensitive_Entailment_Rules}}
HTML
Kouylekov, Milen; Mehdad, Yashar; Negri, Matteo. (2010). "<a href="https://wikipediaquality.com/wiki/Mining_Wikipedia_for_Large-Scale_Repositories_of_Context-Sensitive_Entailment_Rules">Mining Wikipedia for Large-Scale Repositories of Context-Sensitive Entailment Rules</a>".
