The topic-prominence parameter

This article aims to recast the properties of topic-prominent languages and their differences from subject-prominent languages as documented in the functionalist literature into the framework of the Principle-and-Parameter approach. It provides a configurational definition of the topic construction called Topic Phrase (TP), with the topic marker as its head. The availablity of TP enables topic prominent languages to develop various topic structures with properties such as morphological marking; cross-categorial realization of topics and comments; and mutiple application of topicalization. The article elaborates the notion of topic prominence. A topic prominent language is characterized as one that tends to activate the TP and to make full use of the configuration. Typically, it has a larger number and variety of highly grammaticalized topic markers in the Lexicon and permits a variety of syntactic categories to occur in the specifier position and the complement position of TP

Developing a TT-MCTAG for German with an RCG-based parser

Developing linguistic resources, in particular grammars, is known to be a complex task in itself, because of (amongst others) redundancy and consistency issues. Furthermore some languages can reveal themselves hard to describe because of specific characteristics, e.g. the free word order in German. In this context, we present (i) a framework allowing to describe tree-based grammars, and (ii) an actual fragment of a core multicomponent tree-adjoining grammar with tree tuples (TT-MCTAG) for German developed using this framework. This framework combines a metagrammar compiler and a parser based on range concatenation grammar (RCG) to respectively check the consistency and the correction of the grammar. The German grammar being developed within this framework already deals with a wide range of scrambling and extraction phenomena

Complexity of Lexical Descriptions and its Relevance to Partial Parsing

In this dissertation, we have proposed novel methods for robust parsing that integrate the flexibility of linguistically motivated lexical descriptions with the robustness of statistical techniques. Our thesis is that the computation of linguistic structure can be localized if lexical items are associated with rich descriptions (supertags) that impose complex constraints in a local context. However, increasing the complexity of descriptions makes the number of different descriptions for each lexical item much larger and hence increases the local ambiguity for a parser. This local ambiguity can be resolved by using supertag co-occurrence statistics collected from parsed corpora. We have explored these ideas in the context of Lexicalized Tree-Adjoining Grammar (LTAG) framework wherein supertag disambiguation provides a representation that is an almost parse. We have used the disambiguated supertag sequence in conjunction with a lightweight dependency analyzer to compute noun groups, verb groups, dependency linkages and even partial parses. We have shown that a trigram-based supertagger achieves an accuracy of 92.1‰ on Wall Street Journal (WSJ) texts. Furthermore, we have shown that the lightweight dependency analysis on the output of the supertagger identifies 83‰ of the dependency links accurately. We have exploited the representation of supertags with Explanation-Based Learning to improve parsing effciency. In this approach, parsing in limited domains can be modeled as a Finite-State Transduction. We have implemented such a system for the ATIS domain which improves parsing eciency by a factor of 15. We have used the supertagger in a variety of applications to provide lexical descriptions at an appropriate granularity. In an information retrieval application, we show that the supertag based system performs at higher levels of precision compared to a system based on part-of-speech tags. In an information extraction task, supertags are used in specifying extraction patterns. For language modeling applications, we view supertags as syntactically motivated class labels in a class-based language model. The distinction between recursive and non-recursive supertags is exploited in a sentence simplification application

A French Interaction Grammar

International audienceWe present a relatively large coverage French grammar written with the formalism of Interaction Grammars. This formalism combines two key ideas: the grammar is viewed as a constraint system, which is expressed through the notion of tree description, and the resource sensitivity of natural languages is used as a syntactic composition principle by means of a system of polarities. We give an outline of the expressivity of the formalism by modelling significant linguistic phenomena and we show that the grammar architecture provides for re-usability and tractability, which is crucial for building large coverage resources: a modular source grammar is distinguished from the object grammar which results from the compilation of the first one, and the lexicon is independent of the grammar. Finally, we present the results of an evaluation of the grammar achieved with the LEOPAR parser with a test suite of sentences

Encoding a syntactic dictionary into a super granular unification grammar

International audienceWe show how to turn a large-scale syntactic dictionary into a dependency-based unification grammar where each piece of lexical information calls a separate rule, yielding a super granular grammar. Subcategorization, raising and control verbs, auxiliaries and copula, passivization, and tough-movement are discussed. We focus on the semantics-syntax interface and offer a new perspective on syntactic structure

Combining Syntax and Ontologies for Information Extraction

Colloque avec actes et comité de lecture. internationale.International audienceThis paper presents an information extraction system, dedicated to message filtering for a specific domain (security systems). The paper focuses on a method for identifying domain-specific ontology elements (terms and concepts), using syntactic information and an existing domain ontology. The domain ontology is represented using description logics. The system uses description logics inference mechanisms to validate the candidate concepts

Word Ordering as a Graph Rewriting Process

International audienceThis paper shows how the correspondence between a unordered dependency tree and a sentence that expresses it can be achieved by transforming the tree into a string where each linear precedence link corresponds to one specific syntactic relation. We propose a formal grammar with a distributed architecture that can be used for both synthesis and analysis. We argue for the introduction of a topological tree as an intermediate step between dependency syntax and word order

Projecting features and featuring projections

Contains fulltext : 3903.pdf (publisher's version ) (Open Access

Features and projections

Contains fulltext : 14509.pdf (publisher's version ) (Open Access)VIII, 254 p