Summary of the paper
| Title | The Trilingual ALLEGRA Corpus: Presentation and Possible Use for Lexicon Induction |
|---|---|
| Authors | Yves Scherrer and Bruno Cartoni |
| Abstract | In this paper, we present a trilingual parallel corpus for German, Italian and Romansh, a Swiss minority language spoken in the canton of Grisons. The corpus called ALLEGRA contains press releases automatically gathered from the website of the cantonal administration of Grisons. Texts have been preprocessed and aligned with a current state-of-the-art sentence aligner. The corpus is one of the first of its kind, and can be of great interest, particularly for the creation of natural language processing resources and tools for Romansh. We illustrate the use of such a trilingual resource for automatic induction of bilingual lexicons, which is a real challenge for under-represented languages. We induce a bilingual lexicon for German-Romansh by phrase alignment and evaluate the resulting entries with the help of a reference lexicon. We then show that the use of the third language of the corpus ― Italian ― as a pivot language can improve the precision of the induced lexicon, without loss in terms of quality of the extracted pairs. |
| Topics | Corpus (creation, annotation, etc.), Endangered languages, Lexicon, lexical database |
Full paper  |
The Trilingual ALLEGRA Corpus: Presentation and Possible Use for Lexicon Induction |
| Bibtex | @InProceedings{SCHERRER12.685, author = {Yves Scherrer and Bruno Cartoni}, title = {The Trilingual ALLEGRA Corpus: Presentation and Possible Use for Lexicon Induction}, 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} } |