Work

Learning to resolve bridging references

Year: 2004

Type: conference-paper

Abstract: We use machine learning techniques to find the best combination of local focus and lexical distance features for identifying the anchor of mereological bridging references.We find that using first mention, utterance distance, and lexical distance computed using either Google or WordNet results in an accuracy significantly higher than obtained in previous experiments.

Source: Annual Meeting of the Association for Computational Linguistics (ACL)

DOI: 10.3115/1218955.1218974

Authors: Massimo Poesio, Rahul Mehta, Axel Maroudas, Janet Hitzeman

Institutions: University of Essex, Mitre (United States)

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Engineering and Physical Sciences Research Council

OpenAlex ID: W2171549925

FWCI: 4.964

Cites: 27

Cited by: 98

Related to: 10