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From raw text to universal dependencies – Look, no tags! / de Lhoneux, Miryam; Shao, Yan; Basirat, Ali; Kiperwasser, Eliyahu; Stymne, Sara; Goldberg, Yoav; Nivre, Joakim.
Rediger CoNLL 2017 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. Association for Computational Linguistics (ACL), 2017. s. 207-217.
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
de Lhoneux, M, Shao, Y
, Basirat, A, Kiperwasser, E, Stymne, S, Goldberg, Y & Nivre, J 2017,
From raw text to universal dependencies – Look, no tags! i
Rediger CoNLL 2017 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. Association for Computational Linguistics (ACL), s. 207-217, 2017 SIGNLL Conference on Computational Natural Language Learning- CoNLL Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, CoNLL 2017, Vancouver, Canada,
03/08/2017.
https://doi.org/10.18653/v1/k17-3022APA
de Lhoneux, M., Shao, Y.
, Basirat, A., Kiperwasser, E., Stymne, S., Goldberg, Y., & Nivre, J. (2017).
From raw text to universal dependencies – Look, no tags! I
Rediger CoNLL 2017 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies (s. 207-217). Association for Computational Linguistics (ACL).
https://doi.org/10.18653/v1/k17-3022Vancouver
de Lhoneux M, Shao Y
, Basirat A, Kiperwasser E, Stymne S, Goldberg Y o.a.
From raw text to universal dependencies – Look, no tags! I Rediger CoNLL 2017 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. Association for Computational Linguistics (ACL). 2017. s. 207-217
https://doi.org/10.18653/v1/k17-3022Author
de Lhoneux, Miryam ; Shao, Yan ; Basirat, Ali ; Kiperwasser, Eliyahu ; Stymne, Sara ; Goldberg, Yoav ; Nivre, Joakim. / From raw text to universal dependencies – Look, no tags!. Rediger CoNLL 2017 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. Association for Computational Linguistics (ACL), 2017. s. 207-217
Bibtex
@inproceedings{485f08a7ca424c0e96d94ed1e9e48b97,
title = "From raw text to universal dependencies – Look, no tags!",
abstract = "We present the Uppsala submission to the CoNLL 2017 shared task on parsing from raw text to universal dependencies. Our system is a simple pipeline consisting of two components. The first performs joint word and sentence segmentation on raw text; the second predicts dependency trees from raw words. The parser bypasses the need for part-of-speech tagging, but uses word embeddings based on universal tag distributions. We achieved a macro-averaged LAS F1 of 65.11 in the official test run and obtained the 2nd best result for sentence segmentation with a score of 89.03. After fixing two bugs, we obtained an unofficial LAS F1 of 70.49.",
author = "{de Lhoneux}, Miryam and Yan Shao and Ali Basirat and Eliyahu Kiperwasser and Sara Stymne and Yoav Goldberg and Joakim Nivre",
note = "Funding Information: We are grateful to the shared task organizers and to Dan Zeman in particular, and we acknowledge the computational resources provided by CSC in Helsinki and Sigma2 in Oslo through NeIC-NLPL (www.nlpl.eu). Our parser will be made available in the NLPL dependency parsing laboratory. Publisher Copyright: {\textcopyright} 2017 Association for Computational Linguistics.; 2017 SIGNLL Conference on Computational Natural Language Learning- CoNLL Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, CoNLL 2017 ; Conference date: 03-08-2017 Through 04-08-2017",
year = "2017",
doi = "10.18653/v1/k17-3022",
language = "English",
pages = "207--217",
booktitle = "Rediger CoNLL 2017 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies",
publisher = "Association for Computational Linguistics (ACL)",
address = "United States",
}
RIS
TY - GEN
T1 - From raw text to universal dependencies – Look, no tags!
AU - de Lhoneux, Miryam
AU - Shao, Yan
AU - Basirat, Ali
AU - Kiperwasser, Eliyahu
AU - Stymne, Sara
AU - Goldberg, Yoav
AU - Nivre, Joakim
N1 - Funding Information:
We are grateful to the shared task organizers and to Dan Zeman in particular, and we acknowledge the computational resources provided by CSC in Helsinki and Sigma2 in Oslo through NeIC-NLPL (www.nlpl.eu). Our parser will be made available in the NLPL dependency parsing laboratory.
Publisher Copyright:
© 2017 Association for Computational Linguistics.
PY - 2017
Y1 - 2017
N2 - We present the Uppsala submission to the CoNLL 2017 shared task on parsing from raw text to universal dependencies. Our system is a simple pipeline consisting of two components. The first performs joint word and sentence segmentation on raw text; the second predicts dependency trees from raw words. The parser bypasses the need for part-of-speech tagging, but uses word embeddings based on universal tag distributions. We achieved a macro-averaged LAS F1 of 65.11 in the official test run and obtained the 2nd best result for sentence segmentation with a score of 89.03. After fixing two bugs, we obtained an unofficial LAS F1 of 70.49.
AB - We present the Uppsala submission to the CoNLL 2017 shared task on parsing from raw text to universal dependencies. Our system is a simple pipeline consisting of two components. The first performs joint word and sentence segmentation on raw text; the second predicts dependency trees from raw words. The parser bypasses the need for part-of-speech tagging, but uses word embeddings based on universal tag distributions. We achieved a macro-averaged LAS F1 of 65.11 in the official test run and obtained the 2nd best result for sentence segmentation with a score of 89.03. After fixing two bugs, we obtained an unofficial LAS F1 of 70.49.
UR - http://www.scopus.com/inward/record.url?scp=85063163938&partnerID=8YFLogxK
U2 - 10.18653/v1/k17-3022
DO - 10.18653/v1/k17-3022
M3 - Article in proceedings
AN - SCOPUS:85063163938
SP - 207
EP - 217
BT - Rediger CoNLL 2017 - SIGNLL Conference on Computational Natural Language Learning, Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
PB - Association for Computational Linguistics (ACL)
T2 - 2017 SIGNLL Conference on Computational Natural Language Learning- CoNLL Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, CoNLL 2017
Y2 - 3 August 2017 through 4 August 2017
ER -
