Year: 2006
Type: conference-paper
Abstract: In this paper we present an extension of a machine learning based coreference resolution system which uses features induced from different semantic knowledge sources. These features represent knowledge mined from WordNet and Wikipedia, as well as information about semantic role labels. We show that semantic features indeed improve the performance on different referring expression types such as pronouns and common nouns.
Authors: Simone Paolo Ponzetto, Michael Strube
Institution: European Media Laboratory (Germany)
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Funder: Klaus Tschira Stiftung
OpenAlex ID: W2145679919