ISI: Automatic Classification of Relations Between Nominals Using a Maximum Entropy Classifier

Proceedings of the 5th International Workshop on Semantic Evaluation, ACL 2010, pages 222–225, Uppsala, Sweden, 15-16 July 2010. c⃝2010 Association for Computational Linguistics ISI: Automatic Classification of Relations Between Nominals Using a Maximum Entropy Classifier Stephen Tratz and Eduard Hovy Information Sciences Institute University of Southern California Marina del Rey, CA 90292 {stratz,hovy}@isi.edu Abstract The automatic interpretation of semantic relations between nominals is an impor- tant subproblem within natural language understanding applications and is an area of increasing interest. In this paper, we present the system we used to participate in the SEMEVAL 2010 Task 8 Multi-Way Classification of Semantic Relations be- tween Pairs of Nominals. Our system, based upon a Maximum Entropy classifier trained using a large number of boolean features, received the third highest score. 1 Introduction Semantic interpretation of the relations between nominals in text is an area of growing interest within natural language processing (NLP). It has potential uses for a variety of tasks including ma- chine translation (Baldwin and Tanaka, 2004) and question answering (Ahn et al., 2005). The related and more narrowly-focused problem of automatic interpretation of noun compounds is the focus of another SEMEVAL task (Butnariu et al., 2009). In this paper, we discuss the overall setup of SEMEVAL 2010 Task 8 (Hendrickx et al., 2010), present the system we used to participate, and discuss our system’s performance. Our system, which consists of a Maximum Entropy classifier trained using a large variety of boolean features, received the third highest official score of all the entries. 2 Related Work The groundwork for SEMEVAL 2010 Task 8 was laid by an earlier SEMEVAL task (Girju et al., 2007). For SEMEVAL 2007 Task 4, participants provided yes or no answers as to whether a partic- ular relation held for each test example. For SE- MEVAL 2010, instead of providing a binary out- put for a single class, participants were required to perform multi-way classification, that is, select the most appropriate relation from a set of 10 relations including the OTHER relation. The selection of a semantic relation for a pair of nominals within a sentence is somewhat sim- ilar to the task of noun compound interpretation, which is a more restricted problem focused only upon the nouns within noun compounds. Some of the recent work on this problem includes that of Butnariu et al. (2009), Girju (2007), Girju et al. (2005), Kim and Baldwin (2005), Nakov (2008), Nastase et al. (2006), Turney (2006), and Ó Séaghdha and Copestake (2009). 3 Task Overview The task is, given a pair of nominals within their sentence context, select the most appropriate se- mantic relation from the set of available relations and indicate the direction of the relation. Though the final score was based upon the output of the system trained using the whole training dataset, participants were also required to submit three ad- ditional label sets using the first 12.5%, 25%, and 50% of the training data. 3.1 Relation Scheme The relations were taken from earlier work on noun …

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