| LREC 2000 2nd International Conference on Language Resources & Evaluation | ||||||
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| Title | TyPTex: Inductive Typological Text Classification by Multivariate Statistical Analysis for NLP Systems Tuning/Evaluation |
| Authors | Folch Helka (UMR8503 : Analyses de corpus linguistiques, usages et traitements, CNRS / ENS Fontenay/Saint-Cloud, 92211 Saint-Cloud, France, folch@ens-fcl.fr) Heiden Serge (UMR8503 : Analyses de corpus linguistiques, usages et traitements, CNRS / ENS Fontenay/Saint-Cloud, 92211 Saint-Cloud, France, slh@ens-fcl.fr) Habert Benoît (UMR8503 : Analyses de corpus linguistiques, usages et traitements, CNRS / ENS Fontenay/Saint-Cloud, 92211 Saint-Cloud, Francer, habert@limsi.fr) Fleury Serge (UMR8503 : Analyses de corpus linguistiques, usages et traitements, CNRS / ENS Fontenay/Saint-Cloud, 92211 Saint-Cloud, France, fleury@ens-fcl.fr) Illouz Gabriel (LIMSI, CNRS / Université Paris Sud, Orsay, France, illouz@limsi.fr) Lafon Pierre (UMR8503 : Analyses de corpus linguistiques, usages et traitements, CNRS / ENS Fontenay/Saint-Cloud, 92211 Saint-Cloud, France, lafon@ens-fcl.fr) Nioche Julien (UMR8503 : Analyses de corpus linguistiques, usages et traitements, CNRS / ENS Fontenay/Saint-Cloud, 92211 Saint-Cloud, France, nioche@ens-fcl.fr) Prévost Sophie (UMR8503 : Analyses de corpus linguistiques, usages et traitements, CNRS / ENS Fontenay/Saint-Cloud, 92211 Saint-Cloud, France, prevost@ens-fcl.fr) |
| Keywords | Corpus Based Linguistics, Evaluation, Multidimensional Statistics, Natural Language Processing, Software Architectur, Tagging, Text Typology |
| Session | Session WO3 - Corpus Categorisation |
| Full Paper | 254.ps, 254.pdf |
| Abstract | The increasing use of methods in natural language processing (NLP) which are based on huge corpora require that the lexical, morpho-syntactic and syntactic homogeneity of texts be mastered. We have developed a methodology and associate tools for text calibration or ''profiling'' within the ELRA benchmark called ''Contribution to the construction of contemporary french corpora'' based on multivariate analysis of linguistic features. We have integrated these tools within a modular architecture based on a generic model allowing us on the one hand flexible annotation of the corpus with the output of NLP and statistical tools and on the other hand retracing the results of these tools through the annotation layers back to the primary textual data. This allows us to justify our interpretations. |