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Elsa Tolone

Elsa Tolone contributes to research discovery and scholarly infrastructure.

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Computation and Language

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Published work

4 published item(s)

preprint2026arXiv

Conversion of Lexicon-Grammar tables to LMF. Application to French

We describe the first experiment of conversion of Lexicon-Grammar tables for French verbs into the Lexical Markup Framework (LMF) format. The Lexicon-Grammar of the French language is currently one of the major sources of lexical and syntactic information for French. Its conversion into an interoperable representation format according to the LMF standard makes it usable in different contexts, thus contributing to the standardization and interoperability of natural language processing dictionaries. We briefly introduce the Lexicon-Grammar and the derived dictionaries; we analyse the main difficulties faced during the conversion; and we describe the resulting resource.

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preprint2010arXiv

A generic tool to generate a lexicon for NLP from Lexicon-Grammar tables

Lexicon-Grammar tables constitute a large-coverage syntactic lexicon but they cannot be directly used in Natural Language Processing (NLP) applications because they sometimes rely on implicit information. In this paper, we introduce LGExtract, a generic tool for generating a syntactic lexicon for NLP from the Lexicon-Grammar tables. It is based on a global table that contains undefined information and on a unique extraction script including all operations to be performed for all tables. We also present an experiment that has been conducted to generate a new lexicon of French verbs and predicative nouns.

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preprint2010arXiv

Constructions définitoires des tables du Lexique-Grammaire

Lexicon-Grammar tables are a very rich syntactic lexicon for the French language. This linguistic database is nevertheless not directly suitable for use by computer programs, as it is incomplete and lacks consistency. Tables are defined on the basis of features which are not explicitly recorded in the lexicon. These features are only described in literature. Our aim is to define for each tables these essential properties to make them usable in various Natural Language Processing (NLP) applications, such as parsing.

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preprint2010arXiv

Les Entités Nommées : usage et degrés de précision et de désambiguïsation

The recognition and classification of Named Entities (NER) are regarded as an important component for many Natural Language Processing (NLP) applications. The classification is usually made by taking into account the immediate context in which the NE appears. In some cases, this immediate context does not allow getting the right classification. We show in this paper that the use of an extended syntactic context and large-scale resources could be very useful in the NER task.

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