Beyond NomBank: A Study of Implicit Arguments for Nominal Predicates

Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pages 1583–1592, Uppsala, Sweden, 11-16 July 2010. c⃝2010 Association for Computational Linguistics Beyond NomBank: A Study of Implicit Arguments for Nominal Predicates Matthew Gerber and Joyce Y. Chai Department of Computer Science Michigan State University East Lansing, Michigan, USA {gerberm2,jchai}@cse.msu.edu Abstract Despite its substantial coverage, Nom- Bank does not account for all within- sentence arguments and ignores extra- sentential arguments altogether. These ar- guments, which we call implicit, are im- portant to semantic processing, and their recovery could potentially benefit many NLP applications. We present a study of implicit arguments for a select group of frequent nominal predicates. We show that implicit arguments are pervasive for these predicates, adding 65% to the coverage of NomBank. We demonstrate the feasibil- ity of recovering implicit arguments with a supervised classification model. Our re- sults and analyses provide a baseline for future work on this emerging task. 1 Introduction Verbal and nominal semantic role labeling (SRL) have been studied independently of each other (Carreras and M`arquez, 2005; Gerber et al., 2009) as well as jointly (Surdeanu et al., 2008; Hajiˇc et al., 2009). These studies have demonstrated the maturity of SRL within an evaluation setting that restricts the argument search space to the sentence containing the predicate of interest. However, as shown by the following example from the Penn TreeBank (Marcus et al., 1993), this restriction ex- cludes extra-sentential arguments: (1) [arg0 The two companies] [pred produce] [arg1 market pulp, containerboard and white paper]. The goods could be manufactured closer to customers, saving [pred shipping] costs. The first sentence in Example 1 includes the Prop- Bank (Kingsbury et al., 2002) analysis of the ver- bal predicate produce, where arg0 is the agentive producer and arg1 is the produced entity. The sec- ond sentence contains an instance of the nominal predicate shipping that is not associated with argu- ments in NomBank (Meyers, 2007). From the sentences in Example 1, the reader can infer that The two companies refers to the agents (arg0) of the shipping predicate. The reader can also infer that market pulp, containerboard and white paper refers to the shipped entities (arg1 of shipping).1 These extra-sentential arguments have not been annotated for the shipping predi- cate and cannot be identified by a system that re- stricts the argument search space to the sentence containing the predicate. NomBank also ignores many within-sentence arguments. This is shown in the second sentence of Example 1, where The goods can be interpreted as the arg1 of shipping. These examples demonstrate the presence of argu- ments that are not included in NomBank and can- not easily be identified by systems trained on the resource. We refer to these arguments as implicit. This paper presents our study of implicit ar- guments for nominal predicates. We began our study by annotating implicit arguments for a se- lect group of predicates. For these predicates, we found that implicit arguments add 65% to the ex- isting role coverage of …

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