@inproceedings{seddah-candito-2016-hard,
title = "Hard Time Parsing Questions: Building a {Q}uestion{B}ank for {F}rench",
author = "Seddah, Djam{\'e} and
Candito, Marie",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1375",
pages = "2366--2370",
abstract = "We present the French Question Bank, a treebank of 2600 questions. We show that classical parsing model performance drop while the inclusion of this data set is highly beneficial without harming the parsing of non-question data. when facing out-of- domain data with strong structural diver- gences. Two thirds being aligned with the QB (Judge et al., 2006) and being freely available, this treebank will prove useful to build robust NLP systems.",
}
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<abstract>We present the French Question Bank, a treebank of 2600 questions. We show that classical parsing model performance drop while the inclusion of this data set is highly beneficial without harming the parsing of non-question data. when facing out-of- domain data with strong structural diver- gences. Two thirds being aligned with the QB (Judge et al., 2006) and being freely available, this treebank will prove useful to build robust NLP systems.</abstract>
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%0 Conference Proceedings
%T Hard Time Parsing Questions: Building a QuestionBank for French
%A Seddah, Djamé
%A Candito, Marie
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 may
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F seddah-candito-2016-hard
%X We present the French Question Bank, a treebank of 2600 questions. We show that classical parsing model performance drop while the inclusion of this data set is highly beneficial without harming the parsing of non-question data. when facing out-of- domain data with strong structural diver- gences. Two thirds being aligned with the QB (Judge et al., 2006) and being freely available, this treebank will prove useful to build robust NLP systems.
%U https://aclanthology.org/L16-1375
%P 2366-2370
Markdown (Informal)
[Hard Time Parsing Questions: Building a QuestionBank for French](https://aclanthology.org/L16-1375) (Seddah & Candito, LREC 2016)
ACL