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Construction and evaluation of event graphs

Published online by Cambridge University Press:  01 May 2014

GORAN GLAVAŠ  and
JAN ŠNAJDER Open the ORCID record for JAN ŠNAJDER [Opens in a new window]
GORAN GLAVAŠ
Affiliation:
University of Zagreb, Faculty of Electrical Engineering and Computing, Text Analysis and Knowledge Engineering Lab, Unska 3, 10000 Zagreb, Croatia email: [email protected], [email protected]
JAN ŠNAJDER
Affiliation:
University of Zagreb, Faculty of Electrical Engineering and Computing, Text Analysis and Knowledge Engineering Lab, Unska 3, 10000 Zagreb, Croatia email: [email protected], [email protected]
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Abstract

Events play an important role in natural language processing and information retrieval due to numerous event-oriented texts and information needs. Many natural language processing and information retrieval applications could benefit from a structured event-oriented document representation. In this paper, we propose event graphs as a novel way of structuring event-based information from text. Nodes in event graphs represent the individual mentions of events, whereas edges represent the temporal and coreference relations between mentions. Contrary to previous natural language processing research, which has mainly focused on individual event extraction tasks, we describe a complete end-to-end system for event graph extraction from text. Our system is a three-stage pipeline that performs anchor extraction, argument extraction, and relation extraction (temporal relation extraction and event coreference resolution), each at a performance level comparable with the state of the art. We present EvExtra, a large newspaper corpus annotated with event mentions and event graphs, on which we train and evaluate our models. To measure the overall quality of the constructed event graphs, we propose two metrics based on the tensor product between automatically and manually constructed graphs. Finally, we evaluate the overall quality of event graphs with the proposed evaluation metrics and perform a headroom analysis of the system.

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Articles
Information
Natural Language Engineering , Volume 21 , Issue 4 , August 2015 , pp. 607 - 652
Copyright
Copyright © Cambridge University Press 2014 

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