Summary of the paper

Title Ubiquitous Usage of a Broad Coverage French Corpus: Processing the Est Republicain corpus
Authors Djamé Seddah, Marie Candito, Benoit Crabbé and Enrique Henestroza Anguiano
Abstract In this paper, we introduce a set of resources that we have derived from the EST RÉPUBLICAIN CORPUS, a large, freely-available collection of regional newspaper articles in French, totaling 150 million words. Our resources are the result of a full NLP treatment of the EST RÉPUBLICAIN CORPUS: handling of multi-word expressions, lemmatization, part-of-speech tagging, and syntactic parsing. Processing of the corpus is carried out using statistical machine-learning approaches - joint model of data driven lemmatization and part- of-speech tagging, PCFG-LA and dependency based models for parsing - that have been shown to achieve state-of-the-art performance when evaluated on the French Treebank. Our derived resources are made freely available, and released according to the original Creative Common license for the EST RÉPUBLICAIN CORPUS. We additionally provide an overview of the use of these resources in various applications, in particular the use of generated word clusters from the corpus to alleviate lexical data sparseness for statistical parsing.
Topics Corpus (creation, annotation, etc.), Parsing
Full paper Ubiquitous Usage of a Broad Coverage French Corpus: Processing the Est Republicain corpus
Bibtex @InProceedings{SEDDAH12.1130,
  author = {Djamé Seddah and Marie Candito and Benoit Crabbé and Enrique Henestroza Anguiano},
  title = {Ubiquitous Usage of a Broad Coverage French Corpus: Processing the Est Republicain corpus},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
 }
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