Joint Arc-factored Parsing of Syntactic and Semantic Dependencies

Transactions of the Association for Computational Linguistics, 1 (2013) 219–230. Action Editor: Brian Roark. Submitted 1/2013; Revised 3/2013; Published 5/2013. c⃝2013 Association for Computational Linguistics. Joint Arc-factored Parsing of Syntactic and Semantic Dependencies Xavier Llu´ıs and Xavier Carreras and Llu´ıs M`arquez TALP Research Center Universitat Polit`ecnica de Catalunya Jordi Girona 1–3, 08034 Barcelona {xlluis,carreras,lluism}@lsi.upc.edu Abstract In this paper we introduce a joint arc-factored model for syntactic and semantic dependency parsing. The semantic role labeler predicts the full syntactic paths that connect predicates with their arguments. This process is framed as a linear assignment task, which allows to control some well-formedness constraints. For the syntactic part, we define a standard arc-factored dependency model that predicts the full syntactic tree. Finally, we employ dual decomposition techniques to produce consis- tent syntactic and predicate-argument struc- tures while searching over a large space of syntactic configurations. In experiments on the CoNLL-2009 English benchmark we ob- serve very competitive results. 1 Introduction Semantic role labeling (SRL) is the task of identi- fying the arguments of lexical predicates in a sen- tence and labeling them with semantic roles (Gildea and Jurafsky, 2002; M`arquez et al., 2008). SRL is an important shallow semantic task in NLP since predicate-argument relations directly represent se- mantic properties of the type “who” did “what” to “whom”, “how”, and “why” for events expressed by predicates (typically verbs and nouns). Predicate-argument relations are strongly related to the syntactic structure of the sentence: the ma- jority of predicate arguments correspond to some syntactic constituent, and the syntactic structure that connects an argument with the predicate is a strong indicator of its semantic role. Actually, semantic roles represent an abstraction of the syntactic form of a predicative event. While syntactic functions of arguments change with the form of the event (e.g., active vs. passive forms), the semantic roles of argu- ments remain invariant to their syntactic realization. Consequently, since the first works, SRL systems have assumed access to the syntactic structure of the sentence (Gildea and Jurafsky, 2002; Carreras and M`arquez, 2005). A simple approach is to obtain the parse trees as a pre-process to the SRL system, which allows the use of unrestricted features of the syntax. However, as in other pipeline approaches in NLP, it has been shown that the errors of the syn- tactic parser severely degrade the predictions of the SRL model (Gildea and Palmer, 2002). A common approach to alleviate this problem is to work with multiple alternative syntactic trees and let the SRL system optimize over any input tree or part of it (Toutanova et al., 2008; Punyakanok et al., 2008). As a step further, more recent work has proposed parsing models that predict syntactic structure aug- mented with semantic predicate-argument relations (Surdeanu et al., 2008; Hajiˇc et al., 2009; Johansson, 2009; Titov et al., 2009; Llu´ıs et al., 2009), which is the focus of this paper. These joint models should favor the syntactic structure that is most consistent with the semantic predicate-argument structures of a sentence. In principle, …

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