Semantic role labeling of nominalized predicates in Chinese

Proceedings of the Human Language Technology Conference of the North American Chapter of the ACL, pages 431–438, New York, June 2006. c⃝2006 Association for Computational Linguistics Semantic Role Labeling of Nominalized Predicates in Chinese Nianwen Xue Center for Research in Spoken Language University of Colorado Boulder, CO, 80309 Nianwen.Xue@colorado.edu Abstract Recent work on semantic role labeling (SRL) has focused almost exclusively on the analysis of the predicate-argument structure of verbs, largely due to the lack of human-annotated resources for other types of predicates that can serve as train- ing and test data for the semantic role labeling systems. However, it is well- known that verbs are not the only type of predicates that can take arguments. Most notably, nouns that are nominalized forms of verbs and relational nouns gen- erally are also considered to have their own predicate-argument structure. In this paper we report results of SRL experi- ments on nominalized predicates in Chi- nese, using a newly completed corpus, the Chinese Nombank. We also dis- cuss the impact of using publicly avail- able manually annotated verb data to im- prove the SRL accuracy of nouns, exploit- ing a widely-held assumption that verbs and their nominalizations share the same predicate-argument structure. Finally, we discuss the results of applying reranking techniques to improve SRL accuracy for nominalized predicates, which showed in- significant improvement. 1 Introduction Detecting and classifying the arguments of predi- cates has been an active area of research in recent years, driven by the availability of large-scale se- mantically annotated corpora such as the FrameNet (Baker et al., 1998) and the Propbank (Palmer et al., 2005). It is generally formulated as a seman- tic role labeling (SRL) task, where each argument of the predicate is assigned a label that represents the semantic role it plays with regard to its pred- icate (Gildea and Jurafsky, 2002; Hacioglu et al., 2003; Pradhan et al., 2004b; Xue and Palmer, 2004; Toutanova et al., 2005; Koomen et al., 2005). has been the shared task for the CoNLL competitionIt for two consecutive years (Carreras and M`arquez, 2004b; Carreras and M`arquez, 2005). This line of research has also expanded from English to other languages (Sun and Jurafsky, 2004; Xue and Palmer, 2005). So far, however, most of the research efforts have focused on analyzing the predicate-argument structure of verbs, largely due to absence of an- notated data for other predicate types. In this pa- per, we report SRL experiments performed on nom- inalized predicates in Chinese, taking advantage of a newly completed corpus, the Chinese Nombank (Xue, 2006), which we describe in greater detail in Section 2. The rest of the paper is organized as fol- lows. Section 3 describes the architecture of our sys- tem as well as the features we used in our experi- ments. In Section 4 we describe the experimental setups and report our experimental results. We first present experiments that use hand-crafted parses as input, providing a measurement of how well the Nombank annotation can be bootstrapped from the syntactic …

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