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Multilingual semantic role labeling

Björkelund, Anders; Hafdell, Love and Nugues, Pierre LU (2009) In Proceedings of The Thirteenth Conference on Computational Natural Language Learning (CoNLL-2009) p.43-48
Abstract
This paper describes our contribution to the semantic role labeling task (SRL-only) of the CoNLL-2009 shared task in the closed challenge(Hajic et al., 2009). Our system consists of a pipeline of independent, local classifiers

that identify the predicate sense, the arguments of the predicates, and the argument labels. Using these local models, we carried out a beam search to generate a pool of candidates. We then reranked the candidates using a joint learning approach that combines the local models and proposition features.

To address the multilingual nature of the data, we implemented a feature selection procedure that systematically explored the feature space, yielding significant gains over a standard set of features.... (More)
This paper describes our contribution to the semantic role labeling task (SRL-only) of the CoNLL-2009 shared task in the closed challenge(Hajic et al., 2009). Our system consists of a pipeline of independent, local classifiers

that identify the predicate sense, the arguments of the predicates, and the argument labels. Using these local models, we carried out a beam search to generate a pool of candidates. We then reranked the candidates using a joint learning approach that combines the local models and proposition features.

To address the multilingual nature of the data, we implemented a feature selection procedure that systematically explored the feature space, yielding significant gains over a standard set of features. Our system achieved the second best semantic score overall with an average labeled semantic F1 of 80.31. It obtained the best F1 score on the Chinese and German data

and the second best one on English. (Less)
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in
Proceedings of The Thirteenth Conference on Computational Natural Language Learning (CoNLL-2009)
pages
43 - 48
external identifiers
  • scopus:84859994270
language
English
LU publication?
yes
id
7e94d684-fdf1-4e6c-9522-ac8d9ea1f7e1 (old id 1668770)
alternative location
http://www.aclweb.org/anthology/W/W09/W09-1206.pdf
date added to LUP
2010-12-10 12:28:27
date last changed
2017-01-01 08:16:20
@inproceedings{7e94d684-fdf1-4e6c-9522-ac8d9ea1f7e1,
  abstract     = {This paper describes our contribution to the semantic role labeling task (SRL-only) of the CoNLL-2009 shared task in the closed challenge(Hajic et al., 2009). Our system consists of a pipeline of independent, local classifiers<br/><br>
that identify the predicate sense, the arguments of the predicates, and the argument labels. Using these local models, we carried out a beam search to generate a pool of candidates. We then reranked the candidates using a joint learning approach that combines the local models and proposition features.<br/><br>
To address the multilingual nature of the data, we implemented a feature selection procedure that systematically explored the feature space, yielding significant gains over a standard set of features. Our system achieved the second best semantic score overall with an average labeled semantic F1 of 80.31. It obtained the best F1 score on the Chinese and German data<br/><br>
and the second best one on English.},
  author       = {Björkelund, Anders and Hafdell, Love and Nugues, Pierre},
  booktitle    = {Proceedings of The Thirteenth Conference on Computational Natural Language Learning (CoNLL-2009)},
  language     = {eng},
  pages        = {43--48},
  title        = {Multilingual semantic role labeling},
  year         = {2009},
}