Evita: A Robust Event Recognizer For QA Systems

Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), pages 700–707, Vancouver, October 2005. c⃝2005 Association for Computational Linguistics Evita: A Robust Event Recognizer For QA Systems Roser Saur´ı Robert Knippen Marc Verhagen Lab for Linguistics and ComputationJames Pustejovsky Computer Science Department Brandeis University 415 South Street, Waltham, MA 02454, USA �roser,knippen,marc,jamesp �@cs.brandeis.edu Abstract We present Evita, an application for rec- ognizing events in natural language texts. Although developed as part of a suite of tools aimed at providing question answer- ing systems with information about both temporal and intensional relations among events, it can be used independently as an event extraction tool. It is unique in that it is not limited to any pre-established list of relation types (events), nor is it re- stricted to a specific domain. Evita per- forms the identification and tagging of event expressions based on fairly simple strategies, informed by both linguistic- and statistically-based data. It achieves a performance ratio of 80.12% F-measure.1 1 Introduction Event recognition is, after entity recognition, one of the major tasks within Information Extraction. It is currently being succesfully applied in different ar- eas, like bioinformatics and text classification. Rec- ognizing events in these fields is generally carried out by means of pre-defined sets of relations, possi- bly structured into an ontology, which makes such tasks domain dependent, but feasible. Event recog- nition is also at the core of Question Answering, 1This work was supported by a grant from the Advanced Research and Development Activity in Information Technology (ARDA), a U.S. Government entity which sponsors and pro- motes research of import to the Intelligence Community which includes but is not limited to the CIA, DIA, NSA, NIMA, and NRO. since input questions touch on events and situations in the world (states, actions, properties, etc.), as they are reported in the text. In this field as well, the use of pre-defined sets of relation patterns has proved fairly reliable, particularly in the case of factoid type queries (Brill et al., 2002; Ravichandran and Hovy, 2002; Hovy et al., 2002; Soubbotin and Soubbotin, 2002). Nonetheless, such an approach is not sensitive to certain contextual elements that may be fundamental for returning the appropriate answer. This is for in- stance the case in reporting or attempting contexts. Given the passage in (1a), a pattern-generated an- swer to question (1b) would be (1c). Similarly, dis- regarding the reporting context in example (2) could erroneously lead to concluding that no one from the White House was involved in the Watergate affair. (1) a. Of the 14 known ways to reach the summit, only the East Ridge route has never been successfully climbed since George Mallory and Andrew ”Sandy” Irvine first attempted to climb Everest in 1924. b. When did George Mallory and Andrew Irvine first climb Everest? c. #In 1924. (2) a. Nixon claimed that White House counsel John Dean had conducted an investigation into the Watergate matter and found that no-one from the White House was …

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