Alpage: Transition-based Semantic Graph Parsing with Syntactic Features

Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), pages 97–103, Dublin, Ireland, August 23-24, 2014. Alpage: Transition-based Semantic Graph Parsing with Syntactic Features Corentin Ribeyre⋆ ◦ Eric Villemonte de la Clergerie⋆ Djamé Seddah⋆ ⋄ ⋆Alpage, INRIA ◦Univ Paris Diderot, Sorbonne Paris Cité ⋄ Université Paris Sorbonne firstname.lastname@inria.fr Abstract This paper describes the systems deployed by the ALPAGE team to participate to the SemEval-2014 Task on Broad-Coverage Semantic Dependency Parsing. We de- veloped two transition-based dependency parsers with extended sets of actions to handle non-planar acyclic graphs. For the open track, we worked over two orthog- onal axes – lexical and syntactic – in or- der to provide our models with lexical and syntactic features such as word clusters, lemmas and tree fragments of different types. 1 Introduction In recent years, we have seen the emergence of semantic parsing, relying on various tech- niques ranging from graph grammars (Chiang et al., 2013) to transitions-based dependency parsers (Sagae and Tsujii, 2008). Assuming that obtain- ing predicate argument structures is a necessary goal to move from syntax to accurate surface se- mantics, the question of the representation of such structures arises. Regardless of the annotation scheme that should be used, one of the main is- sues of semantic representation is the construction of graph structures, that are inherently harder to generate than the classical tree structures. In that aspect, the shared task’s proposal (Oepen et al., 2014), to evaluate different syntactic- semantic schemes (Ivanova et al., 2012; Hajic et al., 2006; Miyao and Tsujii, 2004) could not ar- rive at a more timely moment when state-of-the-art surface syntactic parsers regularly reach, or cross, a 90% labeled dependency recovery plateau for a This work is licensed under a Creative Commons At- tribution 4.0 International Licence. Page numbers and pro- ceedings footer are added by the organisers. Licence details: http://creativecommons.org/licenses/by/4.0/. wide range of languages (Nivre et al., 2007a; Sed- dah et al., 2013). The two systems we present both extend transition-based parsers in order to be able to gen- erate acyclic dependency graphs. The first one follows the standard greedy search mechanism of (Nivre et al., 2007b), while the second one fol- lows a slightly more global search strategy (Huang and Sagae, 2010; Goldberg et al., 2013) by rely- ing on dynamic programming techniques. In addi- tion to building graphs directly, the main original- ity of our work lies in the use of different kinds of syntactic features, showing that using syntax for pure deep semantic parsing improves global per- formance by more than two points. Although not state-of-the-art, our systems per- form very honorably compared with other single systems in this shared task and pave quite an in- teresting way for further work. In the remainder of this paper, we present the parsers and their ex- tensions for building graphs; we then present our syntactic features and discuss our results. 2 Systems Description Shift-reduce transition-based parsers essentially rely on configurations formed of a stack and a buffer, with stack transitions used …

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