SOTAVerified

Vancouver Welcomes You! Minimalist Location Metonymy Resolution

2017-07-01ACL 2017Code Available0· sign in to hype

Milan Gritta, Mohammad Taher Pilehvar, Nut Limsopatham, Nigel Collier

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

Named entities are frequently used in a metonymic manner. They serve as references to related entities such as people and organisations. Accurate identification and interpretation of metonymy can be directly beneficial to various NLP applications, such as Named Entity Recognition and Geographical Parsing. Until now, metonymy resolution (MR) methods mainly relied on parsers, taggers, dictionaries, external word lists and other handcrafted lexical resources. We show how a minimalist neural approach combined with a novel predicate window method can achieve competitive results on the SemEval 2007 task on Metonymy Resolution. Additionally, we contribute with a new Wikipedia-based MR dataset called RelocaR, which is tailored towards locations as well as improving previous deficiencies in annotation guidelines.

Tasks

Reproductions