Modular Graph Rewriting to Compute Semantics

International audienceTaking an asynchronous perspective on the syntax-semantics interface, we propose to use modular graph rewriting systems as the model of computation. We formally define them and demonstrate their use with a set of modules which produce underspecified semantic representations from a syntactic dependency graph. We experimentally validate this approach on a set of sentences. The results open the way for the production of underspecified semantic dependency structures from corpora annotated with syntactic dependencies and, more generally, for a broader use of modular rewriting systems for computational linguistics

Non-simplifying Graph Rewriting Termination

So far, a very large amount of work in Natural Language Processing (NLP) rely on trees as the core mathematical structure to represent linguistic informations (e.g. in Chomsky's work). However, some linguistic phenomena do not cope properly with trees. In a former paper, we showed the benefit of encoding linguistic structures by graphs and of using graph rewriting rules to compute on those structures. Justified by some linguistic considerations, graph rewriting is characterized by two features: first, there is no node creation along computations and second, there are non-local edge modifications. Under these hypotheses, we show that uniform termination is undecidable and that non-uniform termination is decidable. We describe two termination techniques based on weights and we give complexity bound on the derivation length for these rewriting system.Comment: In Proceedings TERMGRAPH 2013, arXiv:1302.599

Vers un système générique de réécriture de graphes pour l'enrichissement de structures syntaxiques.

National audienceCe travail présente une nouvelle approche pour injecter des dépendances profondes (sujet des verbes à contrôle, partage du sujet en cas d'ellipses, . . .) dans un corpus arboré présentant un schéma d'annotation surfacique et projectif. Nous nous appuyons sur un système de réécriture de graphes utilisant des techniques de programmation par contraintes pour produire des règles génériques qui s'appliquent aux phrases du corpus. Par ailleurs, nous testons la généricité des règles en utilisant des sorties de trois analyseurs syntaxiques différents, afin d'évaluer la dégradation exacte de l'application des règles sur des analyses syntaxiques prédites

A Linguistically-motivated 2-stage Tree to Graph Transformation

International audienceWe propose a new model for transforming dependency trees into target graphs, relying on two distinct stages. During the first stage, standard local tree transformation rules based on patterns are applied to collect a first set of constrained edges to be added to the target graph. In the second stage, motivated by linguistic considerations, the constraints on edges may be used to displace them or their neighbour edges upwards, or to build new mirror edges. The main advantages of this model is to simplify the design of a transformation scheme, with a smaller set of simpler local rules for the first stage, and good properties of termination and confluence for the second level.Nous proposons un nouveau modèle de transformation des arbres de dépendance en graphes, en s'appuyant sur 2 phases distinctes. Durant la première phase, des règles locales classiques de transformation d'arbres, fondées sur des motifs, sont appliquées pour collecter un premier jeu d'arcs avec contraintes devant être ajouté au graphe cible. Dans la seconde phase, motivées par des considérations linguistiques, les contraintes sur les arcs sont utilisées pour déplacer vers le haut ceux-ci ou leurs voisins, ou pour construire des arcs miroir. Les principaux avantages de ce modèle est la simplification la mise au point d'un schéma de transformation, avec un jeu plus réduit de règles locales plus simples, ainsi que de meilleure propriétés de terminaison et de confluence pour le second niveau

Non-size increasing Graph Rewriting for Natural Language Processing

International audienceA very large amount of work in Natural Language Processing use tree structure as the first class citizen mathematical structures to represent linguistic structures such as parsed sentences or feature structures. However, some linguistic phenomena do not cope properly with trees: for instance, in the sentence "Max decides to leave", "Max" is the subject of the both predicates "to decide" and "to leave". Tree-based linguistic formalisms generally use some encoding to manage sentences like the previous example. In former papers, we discussed the interest to use graphs rather than trees to deal with linguistic structures and we have shown how Graph Rewriting could be used for their processing, for instance in the transformation of the sentence syntax into its semantics. Our experiments have shown that Graph Rewriting applications to Natural Language Processing do not require the full computational power of the general Graph Rewriting setting. The most important observation is that all graph vertices in the final structures are in some sense "predictable" from the input data and so, we can consider the framework of Non-size increasing Graph Rewriting. In our previous papers, we have formally described the Graph Rewriting calculus we used and our purpose here is to study the theoretical aspect of termination with respect to this calculus. In our framework, we show that uniform termination is undecidable and that non-uniform termination is decidable. We define termination techniques based on weight, we prove the termination of weighted rewriting systems and we give complexity bounds on derivation lengths for these rewriting systems