Work

Inferring Sentence-internal Temporal Relations

Year: 2004

Type: conference-paper

Abstract: In this paper we propose a data intensive approach for inferring sentence-internal temporal relations, which relies on a simple probabilistic model and assumes no manual coding. We explore various combinations of features, and evaluate performance against a gold-standard corpus and human subjects performing the same task. The best model achieves 70.7% accuracy in inferring the temporal relation between two clauses and 97.4% accuracy in ordering them, assuming that the temporal relation is known.

Source: Edinburgh Research Explorer (University of Edinburgh)

Authors: Mirella Lapata, Alex Lascarides

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Engineering and Physical Sciences Research Council

OpenAlex ID: W42350778

FWCI: 5.395

Cites: 23

Cited by: 62

Related to: 20