@inproceedings{ramos-etal-2010-towards,
title = "Towards a Motivated Annotation Schema of Collocation Errors in Learner Corpora",
author = "Ramos, Margarita Alonso and
Wanner, Leo and
Vincze, Orsolya and
del Bosque, Gerard Casamayor and
Veiga, Nancy V{\'a}zquez and
Su{\'a}rez, Estela Mosqueira and
Gonz{\'a}lez, Sabela Prieto",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/751_Paper.pdf",
abstract = "Collocations play a significant role in second language acquisition. In order to be able to offer efficient support to learners, an NLP-based CALL environment for learning collocations should be based on a representative collocation error annotated learner corpus. However, so far, no theoretically-motivated collocation error tag set is available. Existing learner corpora tag collocation errors simply as lexical errors ― which is clearly insufficient given the wide range of different collocation errors that the learners make. In this paper, we present a fine-grained three-dimensional typology of collocation errors that has been derived in an empirical study from the learner corpus CEDEL2 compiled by a team at the Autonomous University of Madrid. The first dimension captures whether the error concerns the collocation as a whole or one of its elements; the second dimension captures the language-oriented error analysis, while the third exemplifies the interpretative error analysis. To facilitate a smooth annotation along this typology, we adapted Knowtator, a flexible off-the-shelf annotation tool implemented as a Prot{\'e}g{\'e} plugin.",
}
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<abstract>Collocations play a significant role in second language acquisition. In order to be able to offer efficient support to learners, an NLP-based CALL environment for learning collocations should be based on a representative collocation error annotated learner corpus. However, so far, no theoretically-motivated collocation error tag set is available. Existing learner corpora tag collocation errors simply as lexical errors ― which is clearly insufficient given the wide range of different collocation errors that the learners make. In this paper, we present a fine-grained three-dimensional typology of collocation errors that has been derived in an empirical study from the learner corpus CEDEL2 compiled by a team at the Autonomous University of Madrid. The first dimension captures whether the error concerns the collocation as a whole or one of its elements; the second dimension captures the language-oriented error analysis, while the third exemplifies the interpretative error analysis. To facilitate a smooth annotation along this typology, we adapted Knowtator, a flexible off-the-shelf annotation tool implemented as a Protégé plugin.</abstract>
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%0 Conference Proceedings
%T Towards a Motivated Annotation Schema of Collocation Errors in Learner Corpora
%A Ramos, Margarita Alonso
%A Wanner, Leo
%A Vincze, Orsolya
%A del Bosque, Gerard Casamayor
%A Veiga, Nancy Vázquez
%A Suárez, Estela Mosqueira
%A González, Sabela Prieto
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F ramos-etal-2010-towards
%X Collocations play a significant role in second language acquisition. In order to be able to offer efficient support to learners, an NLP-based CALL environment for learning collocations should be based on a representative collocation error annotated learner corpus. However, so far, no theoretically-motivated collocation error tag set is available. Existing learner corpora tag collocation errors simply as lexical errors ― which is clearly insufficient given the wide range of different collocation errors that the learners make. In this paper, we present a fine-grained three-dimensional typology of collocation errors that has been derived in an empirical study from the learner corpus CEDEL2 compiled by a team at the Autonomous University of Madrid. The first dimension captures whether the error concerns the collocation as a whole or one of its elements; the second dimension captures the language-oriented error analysis, while the third exemplifies the interpretative error analysis. To facilitate a smooth annotation along this typology, we adapted Knowtator, a flexible off-the-shelf annotation tool implemented as a Protégé plugin.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/751_Paper.pdf
Markdown (Informal)
[Towards a Motivated Annotation Schema of Collocation Errors in Learner Corpora](http://www.lrec-conf.org/proceedings/lrec2010/pdf/751_Paper.pdf) (Ramos et al., LREC 2010)
ACL
- Margarita Alonso Ramos, Leo Wanner, Orsolya Vincze, Gerard Casamayor del Bosque, Nancy Vázquez Veiga, Estela Mosqueira Suárez, and Sabela Prieto González. 2010. Towards a Motivated Annotation Schema of Collocation Errors in Learner Corpora. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).