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From news to comment: Resources and benchmarks for parsing the language of web 2.0

Foster, Jennifer and Cetinoglu, Ozlem and Wagner, Joachim and Le Roux, Joseph and Nivre, Joakim and Hogan, Deirdre and VanGenabith, Josef (2011) From news to comment: Resources and benchmarks for parsing the language of web 2.0. In: The 5th International Joint Conference on Natural Language Processing (IJCNLP), 08-13 Nov 2011, Chiang Mai, Thailand. ISBN 978-974-466-564-5

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Abstract

We investigate the problem of parsing the noisy language of social media. We evaluate four all-Street-Journal-trained statistical parsers (Berkeley, Brown, Malt and MST) on a new dataset containing 1,000 phrase structure trees for sentences from microblogs (tweets) and discussion forum posts. We compare the four parsers on their ability to produce Stanford dependencies for these Web 2.0 sentences. We find that the parsers have a particular problem with tweets and that a substantial part of this problem is related to POS tagging accuracy. We attempt three retraining experiments involving Malt, Brown and an in-house Berkeley-style parser and obtain a statistically significant improvement for all three parsers.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Parsing; domain adaptation; self-training; up-training; user-generated content; twitter
Subjects:Computer Science > Computational linguistics
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
Research Initiatives and Centres > National Centre for Language Technology (NCLT)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in:Proceedings of the 5th International Joint Conference on Natural Language Processing (IJCNLP). . Asian Federation of Natural Language Processing. ISBN 978-974-466-564-5
Publisher:Asian Federation of Natural Language Processing
Official URL:http://www.ijcnlp2011.org/proceeding/IJCNLP2011-MAIN/index.html
Copyright Information:©2011 Asian Federation of Natural Language Processing
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Enterprise Ireland, Science Foundation Ireland, French Agence Nationale pour la Recherche
ID Code:16854
Deposited On:28 Feb 2012 15:43 by Joachim Wagner. Last Modified 30 May 2012 10:28

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