Constraint-Based Event Recognition for Information Extraction

CONSTRAINT-BASED EVENT RECOGNITION FOR INFORMATION EXTRACTION Jeremy Crowe* Department of Artificial Intelligence Edinburgh University Edinburgh, EH1 1HN UK j.crowe@ed.ac.uk Abstract Event recognition We present a program for segmenting texts ac- cording to the separate events they describe. A modular architecture is described that al- lows us to examine the contributions made by particular aspects of natural language to event structuring. This is applied in the context of terrorist news articles, and a technique is sug- gested for evaluating the resulting segmenta- tions. We also examine the usefulness of vari- ous heuristics in forming these segmentations. Introduction One of the issues to emerge from recent evaluations of information extraction systems (Sundheim, 1992) is the importance of discourse processing (Iwafiska et al., 1991) and, in particular, the ability to recognise multiple events in a text. It is this task that we address here. We are developing a program that assigns message- level event structures to newswire texts. Although the need to recognise events has been widely acknowledged, most approaches to information extraction (IE) perform this task either as a part of template merging late in the IE process (Grishman and Sterling, 1993) or, in a few cases, as an integral part of some deeper reasoning mechanism (e.g. (Hobbs et al., 1991)). Our approach is based on the assumption that dis- course processing should be done early in the informa- tion extraction process. This is by no means a new idea. The arguments in favour of an early discourse segmen- tation are well known - easier coreference of entities, a reduced volume of text to be subjected to necessarily deeper analysis, and so on. Because of this early position in the IE process, an event recognition program is faced with a necessarily shallow textual representation. The purpose of our work is, therefore, to investigate the quality of text segmenta- tion that is possible given such a surface form. *I would like to thank Chris Mellish and the anony- mous referees for their helpful comments. Supported by a grant from the ESRC. What is an event? If we are to distinguish between events, it is important that we know what they look like. This is harder than it might at first seem. A closely related (though not identical) problem is found in recognising boundaries in discourse, and there seems to be little agreement in the literature as to the properties and functions they pos- sess (Morris and Hirst, 1991), (Grosz and Sidner, 1986). Our system is aimed at documents typified by those in the MUC-4 corpus (Sundheim, 1992). These deal with Latin American terrorist incidents, and vary widely in terms of origin, medium and purpose. In the task description for the MUC-4 evaluation, two events are deemed to be distinct if they describe either multiple types of incident or multiple instances of a particular type of incident, where instances are distinguished by having different locations, dates, categories or perpetra- tors. (NRaD, 1992) Although this definition suffers from a certain amount of circularity, it nonetheless …

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