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SemEval-2015 Task 5: QA TempEval - Evaluating Temporal Information Understanding with Question Answering

Year: 2015

Type: conference-paper

Abstract: QA TempEval shifts the goal of previous TempEvals away from an intrinsic evaluation methodology toward a more extrinsic goal of question answering.This evaluation requires systems to capture temporal information relevant to perform an end-user task, as opposed to corpus-based evaluation where all temporal information is equally important.Evaluation results show that the best automated TimeML annotations reach over 30% recall on questions with 'yes' answer and about 50% on easier questions with 'no' answers.Features that helped achieve better results are event coreference and a time expression reasoner.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.18653/v1/s15-2134

Authors: Hector Llorens, Nathanael Chambers, Naushad UzZaman, Nasrin Mostafazadeh, James Allen, James Pustejovsky

Institutions: University of Alicante, United States Naval Academy, Nuance Communications (United States), University of Rochester, Florida Institute for Human and Machine Cognition, Brandeis University

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W2112251443

FWCI: 4.175

Cites: 10

Cited by: 55

Related to: 10