Recognizing lexical inferences between pairs of terms is a common task in NLP applications, which should typically be performed within a given context. Such context-sensitive inferences have to consider both term meaning in context as well as the fine-grained relation holding between the terms. Hence, to develop suitable lexical inference methods, we need datasets that are annotated with fine-grained semantic relations in-context. Since existing datasets either provide outof- context annotations or refer to coarsegrained relations, we propose a methodology for adding context-sensitive annotations. We demonstrate our methodology by applying it to phrase pairs from PPDB 2.0, creating a novel dataset of finegrained lexical inferences in-context and showing its utility in developing contextsensitive methods.
|Title of host publication||*SEM 2016 - 5th Joint Conference on Lexical and Computational Semantics, Proceedings|
|Publisher||Association for Computational Linguistics (ACL)|
|Number of pages||6|
|State||Published - 2016|
|Event||5th Joint Conference on Lexical and Computational Semantics, *SEM 2016 - Berlin, Germany|
Duration: 11 Aug 2016 → 12 Aug 2016
|Name||*SEM 2016 - 5th Joint Conference on Lexical and Computational Semantics, Proceedings|
|Conference||5th Joint Conference on Lexical and Computational Semantics, *SEM 2016|
|Period||11/08/16 → 12/08/16|
Bibliographical noteFunding Information:
This work was partially supported by an Intel ICRI-CI grant, the Israel Science Foundation grant 880/12, and the German Research Foundation through the German-Israeli Project Cooperation (DIP, grant DA 1600/1-1).