TY - GEN
T1 - A pipeline approach for syntactic and semantic dependency parsing
AU - Watanabe, Yotaro
AU - Iwatate, Masakazu
AU - Asahara, Masayuki
AU - Matsumoto, Yuji
PY - 2008
Y1 - 2008
N2 - This paper describes our system for syntactic and semantic dependency parsing to participate the shared task of CoNLL-2008. We use a pipeline approach, in which syntactic dependency parsing, word sense disambiguation, and semantic role labeling are performed separately: Syntactic dependency parsing is performed by a tournament model with a support vector machine; word sense disambiguation is performed by a nearest neighbour method in a compressed feature space by probabilistic latent semantic indexing; and semantic role labeling is performed by a an online passive-aggressive algorithm. The submitted result was 79.10 macroaverage F1 for the joint task, 87.18% syntactic dependencies LAS, and 70.84 semantic dependencies F1. After the deadline, we constructed the other configuration, which achieved 80.89 F1 for the joint task, and 74.53 semantic dependencies F1. The result shows that the configuration of pipeline is a crucial issue in the task.
AB - This paper describes our system for syntactic and semantic dependency parsing to participate the shared task of CoNLL-2008. We use a pipeline approach, in which syntactic dependency parsing, word sense disambiguation, and semantic role labeling are performed separately: Syntactic dependency parsing is performed by a tournament model with a support vector machine; word sense disambiguation is performed by a nearest neighbour method in a compressed feature space by probabilistic latent semantic indexing; and semantic role labeling is performed by a an online passive-aggressive algorithm. The submitted result was 79.10 macroaverage F1 for the joint task, 87.18% syntactic dependencies LAS, and 70.84 semantic dependencies F1. After the deadline, we constructed the other configuration, which achieved 80.89 F1 for the joint task, and 74.53 semantic dependencies F1. The result shows that the configuration of pipeline is a crucial issue in the task.
UR - http://www.scopus.com/inward/record.url?scp=84865094973&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84865094973&partnerID=8YFLogxK
U2 - 10.3115/1596324.1596365
DO - 10.3115/1596324.1596365
M3 - Conference contribution
AN - SCOPUS:84865094973
SN - 1905593481
SN - 9781905593484
T3 - CoNLL 2008 - Proceedings of the Twelfth Conference on Computational Natural Language Learning
SP - 228
EP - 232
BT - CoNLL 2008 - Proceedings of the Twelfth Conference on Computational Natural Language Learning
PB - Association for Computational Linguistics (ACL)
T2 - 12th Conference on Computational Natural Language Learning, CoNLL 2008
Y2 - 16 August 2008 through 17 August 2008
ER -