Vancouver Welcomes You! Minimalist Location Metonymy Resolution

نویسندگان

  • Milan Gritta
  • Mohammad Taher Pilehvar
  • Nut Limsopatham
  • Nigel Collier
چکیده

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.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

UP13: Knowledge-poor Methods (Sometimes) Perform Poorly

This short paper presents a system developed at the Université Paris 13 for the Semeval 2007 Metonymy Resolution Task (task #08, location name track; see Markert and Nissim, 2007). The system makes use of plain word forms only. In this paper, we evaluate the accuracy of this minimalist approach, compare it to a more complex one which uses both syntactic and semantic features, and discuss its us...

متن کامل

Metonymy Resolution as a Classification Task

We reformulate metonymy resolution as a classification task. This is motivated by the regularity of metonymic readings and makes general classification and word sense disambiguation methods available for metonymy resolution. We then present a case study for location names, presenting both a corpus of location names annotated for metonymy as well as experiments with a supervised classification a...

متن کامل

Metonimy resolution for named entities: an hybrid approach

Named Entity metonymy resolution is a challenging natural langage processing task, which has been recently subject to a growing interest. In this paper, we describe the method we have developed in order to solve Named entity metonymy in the framework of the SemEval 2007 competition. In order to perform Named Entity metonymy resolution on location names and company names, as required for this ta...

متن کامل

XRCE-M: A Hybrid System for Named Entity Metonymy Resolution

This paper is an extended version of (Brun et al., 2007) describing our participation to the Metonymy Resolution (task #8) at SemEval 2007. In order to perform Named Entity metonymy resolution on location names and company names, as required for this task, we developed a hybrid system based on the use of a robust parser that extracts deep syntactic relations combined with a non supervised distr...

متن کامل

FUH (FernUniversität in Hagen): Metonymy Recognition Using Different Kinds of Context for a Memory-Based Learner

For the metonymy resolution task at SemEval-2007, the use of a memory-based learner to train classifiers for the identification of metonymic location names is investigated. Metonymy is resolved on different levels of granularity, differentiating between literal and non-literal readings on the coarse level; literal, metonymic, and mixed readings on the medium level; and a number of classes cover...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017