Articles

ion of grammatical formalisms as methods for lexical disambiguation Guillaume Bonfante and Bruno Guillaume and Guy Perrier LORIA - UMR 7503, Campus Scientifique, B.P. 239, F-54506 Vandœuvre l`es Nancy CEDEX {Guillaume.Bonfante, Bruno.Guillaume, Guy.Perrier}@loria.fr Abstract In the context of lexicalized grammars, we propose general methods for lexical disam- biguation based on …...

In this paper, we present an approach to include morpho-syntactic dependencies into the training of the statistical alignment models. Existing statistical translation sys- tems usually treat different derivations of the same base form as they were indepen- dent of each other. We propose a method which explicitly takes into account …...

In this paper we present a grammar formalism that combines the insights from Combinatory Categorial Grammar with feature structure unification. We show how information structure can be incorporated with syntactic and semantic representations in a principled way. We focus on the way theme, rheme, and focus are integrated in the …...

This paper shows how talking robots can be built from off-the-shelf components, based on the Lego MindStorms robotics platform. We present four robots that students created as final projects in a seminar we supervised. Because Lego robots are so affordable, we argue that it is now feasible for any dialogue …...

Word dependency is important in parsing tech- nology. Some applications such as Informa- tion Extraction from biological documents ben- efit from word dependency analysis even with- out phrase labels. Therefore, we expect an ac- curate dependency analyzer trainable without using phrase labels is useful. Although such an English word dependency …...

It is argued in this paper that an optimal solution to disambiguation is a combination of linguistically motivated rules and resolution based on probability or heuristic rules. By disambiguation is here meant ambiguity resolution on all levels of language analysis, including morphology and semantics. The discussion is based on Swahili, …...

We suggest a new goal and evaluation criterion for word similarity measures. The new criterion - meaning-entailing substitutability - fits the needs of semantic-oriented NLP applications and can be evaluated directly (independent of an application) at a good level of human agreement. Motivated by this semantic criterion we analyze the …...

This paper describes the role of supertagging in a wide-coverage CCG parser which uses a log-linear model to select an analysis. The supertagger reduces the derivation space over which model estimation is performed, reducing the space required for discriminative training. It also dramatically increases the speed of the parser. We …...

This paper presents a machine learning approach to bare sluice disambiguation in dialogue. We ex- tract a set of heuristic principles from a corpus-based sample and formulate them as probabilistic Horn clauses. We then use the predicates of such clauses to create a set of domain independent features to an- …...

Traditionally, coreference resolution is done by mining the reference relationships be- tween NP pairs. However, an individual NP usually lacks adequate description informa- tion of its referred entity. In this paper, we propose a supervised learning-based ap- proach which does coreference resolution by exploring the relationships between NPs and coreferential …...

In this paper, we address the word alignment problem for statistical machine translation. We aim at creating a sym- metric word alignment allowing for reli- able one-to-many and many-to-one word relationships. We perform the iterative alignment training in the source-to-target and the target-to-source direction with the well-known IBM and HMM …...

Word alignment is a challenging task aim- ing at the identification of translational re- lations between words and multi-word units in parallel corpora. Many alignment strate- gies are based on links between single words. Different strategies can be used to find the optimal word alignment using such one-to- one word …...

In statistical machine translation, the gen- eration of a translation hypothesis is com- putationally expensive. If arbitrary re- orderings are permitted, the search prob- lem is NP-hard. On the other hand, if we restrict the possible reorderings in an appropriate way, we obtain polynomial-time search algorithm. We in-a vestigate different …...

Anaphora in Texts and Dialogues Costanza Navarretta Center for Sprogteknologi, University of Copenhagen Njalsgade 80 2300 Copenhagen S costanza@cst.dk Abstract This paper describes an extension of the dar-algorithm (Navarretta, 2004) for re- solving intersentential pronominal anaphors referring to individual and abstract enti- ties in texts and dialogues. In dar indi- …...

We extend Combinatory Categorial Grammar (CCG) with a generalized notion of multi- dimensional sign, inspired by the types of rep- resentations found in constraint-based frame- works like HPSG or LFG. The generalized sign allows multiple levels to share information, but only in a resource-bounded way through a very restricted indexation …...

In this paper we describe a method of automati- cally learning domain theories from parsed cor- pora of sentences from the relevant domain and use FSA techniques for the graphical represen- tation of such a theory. By a ‘domain theory’ we mean a collection of facts and generalisations or rules …...

We propose a syntax-semantics interface that realises the mapping between syntax and se- mantics as a relation and does not make func- tionality assumptions in either direction. This interface is stated in terms of Extensible De- pendency Grammar (XDG), a grammar formal- ism we newly specify. XDG’s constraint-based parser supports …...

Linearization-based HPSG theories are widely used for analyzing languages with relatively free constituent order. This paper introduces the Generalized ID/LP (GIDLP) grammar for- mat, which supports a direct encoding of such theories, and discusses key aspects of a parser that makes use of the dominance, precedence, and linearization domain information …...

An efficient bit-vector-based CKY-style parser for context-free parsing is presented. The parser computes a compact parse forest representation of the complete set of possible analyses for large treebank grammars and long input sen- tences. The parser uses bit-vector operations to parallelise the basic parsing operations. The parser is particularly useful …...

Statistical language modeling remains a challeng- ing task, in particular for morphologically rich lan- guages. Recently, new approaches based on factored language models have been developed to address this problem. These models provide principled ways of including additional conditioning variables other than the preceding words, such as morphological or syntactic …...