Summary of the paper

Title Semantic annotation of French corpora: animacy and verb semantic classes
Authors Juliette Thuilier and Laurence Danlos
Abstract This paper presents a first corpus of French annotated for animacy and for verb semantic classes. The resource consists of 1,346 sentences extracted from three different corpora: the French Treebank (Abeillé and Barrier, 2004), the Est-Républicain corpus (CNRTL) and the ESTER corpus (ELRA). It is a set of parsed sentences, containing a verbal head subcategorizing two complements, with annotations on the verb and on both complements, in the TIGER XML format (Mengel and Lezius, 2000). The resource was manually annotated and manually corrected by three annotators. Animacy has been annotated following the categories of Zaenen et al. (2004). Measures of inter-annotator agreement are good (Multi-pi = 0.82 and Multi-kappa = 0.86 (k = 3, N = 2360)). As for verb semantic classes, we used three of the five levels of classification of an existing dictionary: 'Les Verbes du Français' (Dubois and Dubois-Charlier, 1997). For the higher level (generic classes), the measures of agreement are Multi-pi = 0.84 and Multi-kappa = 0.87 (k = 3, N = 1346). The inter-annotator agreements show that the annotated data are reliable for both animacy and verbal semantic classes.
Topics Corpus (creation, annotation, etc.), Semantics
Full paper Semantic annotation of French corpora: animacy and verb semantic classes
Bibtex @InProceedings{THUILIER12.552,
  author = {Juliette Thuilier and Laurence Danlos},
  title = {Semantic annotation of French corpora: animacy and verb semantic classes},
  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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