Skip to main content
SpringerLink
Log in
Book cover

Trends in Parsing Technology pp 57–68Cite as

Dependency Parsing and Domain Adaptation with Data-Driven LR Models and Parser Ensembles

  • Chapter
  • First Online:

Part of the book series: Text, Speech and Language Technology ((TLTB,volume 43))

Abstract

Natural language parsing with data-driven dependency-based frameworks has received an increasing amount of attention in recent years, as observed in the shared tasks hosted by the Conference on Computational Natural Language Learning (CoNLL) in 2006 (Buchholz and Marsi, 2006) and 2007 (Nivre et al., 2007).

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    We append a “virtual root” word to the beginning of every sentence, which is used as the head of every word in the dependency structure that does not have a head in the sentence.

  2. 2.

    The larger third set was not used.

References

  • Abeillé, A. (Ed.) (2003). Treebanks: Building and Using Parsed Corpora. Dordrecht: Kluwer.

    Google Scholar 

  • Aduriz, I., M.J. Aranzabe, J.M. Arriola, A. Atutxa, A.D. de Ilarraza, A. Garmendia, and M. Oronoz (2003). Construction of a Basque dependency treebank. In Proceedings of the 2nd Workshop on Treebanks and Linguistic Theories (TLT), Växjö, Sweden, pp. 201–204.

    Google Scholar 

  • Berger, A., S.A.D. Pietra, and V.J.D. Pietra (1996). A maximum entropy approach to natural language processing. Computational Linguistics 22(1), 39–71.

    Google Scholar 

  • Böhmová, A., J. Hajič, E. Hajičová, and B. Hladká (2003). The PDT: a 3-level annotation scenario. In Abeillé (2003), Chapter 7, pp. 103–127.

  • Briscoe, E. and J. Carroll (1993). Generalized probabilistic lr parsing of natural language (corpora) with unification-based grammars. Computational Linguistics 19(1), 25–59.

    Google Scholar 

  • Brown, R. (1973). A First Language: The Early Stages. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Buchholz, S. and E. Marsi (2006). CoNLL-X shared task on multilingual dependency parsing. In Proceedings of the CoNLL-X Shared Task. Tenth Conference on Computational Natural Language Learning (CoNLL-X), New York, NY, pp. 149–164.

    Google Scholar 

  • Chen, K., C. Luo, M. Chang, F. Chen, C. Chen, C. Huang, and Z. Gao (2003). Sinica treebank: design criteria, representational issues and implementation. In Abeillé (2003), Chapter 13, pp. 231–248.

  • Csendes, D., J. Csirik, T. GyimÓthy, and A. Kocsor (2005). The Szeged Treebank. Berlin: Springer.

    Google Scholar 

  • Daelemans, W. and A.V. den Bosch, (2005). Memory-Based Language Processing. Cambridge: Cambridge Press.

    Book  Google Scholar 

  • Erkan, G., A. Ozgur, and D. Radev (2007). Semisupervised classification for extracting protein interaction sentences using dependency parsing. In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), Prague, Czech Republic, pp. 228–237.

    Google Scholar 

  • Hajič, J., O. Smrž, P. Zemánek, J. Šnaidauf, and E. Beška (2004). Prague Arabic dependency treebank: development in data and tools. In Proceedings of the NEMLAR International Conference on Arabic Language Resources and Tools, Cairo, Egypt, pp. 110–117.

    Google Scholar 

  • Johansson, R. and P. Nugues (2007). Extended constituent-to-dependency conversion for English. In Proceedings of the 16th Nordic Conference on Computational Linguistics (NODALIDA), Tartu, Estonia, pp. 105–112.

    Google Scholar 

  • Kazama, J. and J. Tsujii (2003). Evaluation and extension of maximum entropy models with inequality constraints. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, Sapporo, Japan, pp. 137–144.

    Google Scholar 

  • Knuth, D. (1965). On the translation of languages from left to right. Information and Control 8, 607–639.

    Article  Google Scholar 

  • Koo, T., X. Carreras, and M. Collins (2008). Simple semi-supervised dependency parsing. In Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics (ACL), Columbus, OH, pp. 595–603.

    Google Scholar 

  • Kulick, S., A. Bies, M. Liberman, M. Mandel, R. McDonald, M. Palmer, A. Schein, and L. Ungar (2004). Integrated annotation for biomedical information extraction. In Proceedings of BioLINK 2004: Linking Biological Literature, Ontologies and Databases, Boston, MA, pp. 61–68.

    Google Scholar 

  • MacWhinney, B. (2000). The CHILDES Project: Tools for Analyzing Talk. Mahwah, NJ: Lawrence Erlbaum.

    Google Scholar 

  • Marcus, M., B. Santorini, and M. Marcinkiewicz (1993). Building a large annotated corpus of English: the Penn Treebank. Computational Linguistics 19(2), 313–330.

    Google Scholar 

  • Martí, M.A., M. Taulé, L. Màrquez, and M. Bertran (2007). CESS-ECE: A multilingual and multilevel annotated corpus. Available for download from: http://www.lsi.upc.edu/mbertran/cessece/

  • McClosky, D., E. Charniak, and M. Johnson (2006). Effective self-training for parsing. In Proceedings of the 2006 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics (HLT-NAACL), New York, NY, pp. 152–159.

    Google Scholar 

  • McDonald, R., F. Pereira, K. Ribarov, and J. Hajič (2005). Non-projective dependency parsing using spanning tree algorithms. In Proceedings of the Human Language Technology Conference and the Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), Vancouver, BC, pp. 523–530.

    Google Scholar 

  • Montemagni, S., F. Barsotti, M. Battista, N. Calzolari, O. Corazzari, A. Lenci, A. Zampolli, F. Fanciulli, M. Massetani, R. Raffaelli, R. Basili, M.T. Pazienza, D. Saracino, F. Zanzotto, N. Nana, F. Pianesi, and R. Delmonte (2003). Building the Italian syntactic-semantic treebank. In Abeillé (2003), Chapter 11, pp. 189–210.

  • Nivre, J. (2003). An efficient algorithm for projective dependency parsing. In Proceedings of the 8th International Workshop on Parsing Technologies, Nancy, France, pp. 149–160.

    Google Scholar 

  • Nivre, J. (2004). Incrementality in deterministic dependency parsing. In Proceedings of the ACL Workshop on Incremental Parsing: Bringing Engineering and Cognition Together (Workshop at ACL-2004), Barcelona, Spain, pp. 50–57.

    Google Scholar 

  • Nivre, J. and J. Nilsson (2005). Pseudo-projective dependency parsing. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL), pp. 99–106.

    Google Scholar 

  • Nivre, J. and M. Scholz (2004). Deterministic dependency parsing of English text. In Proceedings of the 20th International Conference on Computational Linguistics (COLING), Geneva, Switzerland, pp. 64–70.

    Google Scholar 

  • Nivre, J., J. Hall, S. Kübler, R. McDonald, J. Nilsson, S. Riedel, and D. Yuret (2007). The CoNLL 2007 shared task on dependency parsing. In Proceedings of the CoNLL 2007 Shared Task. Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), Prague, Czech Republic, pp. 915–932.

    Google Scholar 

  • Oflazer, K., B. Say, D.Z. Hakkani-Tür, and G. Tür (2003). Building a Turkish treebank. In Abeillé (2003), Chapter 15, pp. 261–277.

  • Platt, J. (2000). Probabilities for SV machines. In A. Smola, P. Bartlett, B. Scholkopf, and D. Schuurmans (Eds.), Advances in Large Margin Classifiers. Cambridge, MA: MIT Press, pp. 61–74.

    Google Scholar 

  • Prokopidis, P., E. Desypri, M. Koutsombogera, H. Papageorgiou, and S. Piperidis (2005). Theoretical and practical issues in the construction of a Greek dependency treebank. In Proceedings of the 4th Workshop on Treebanks and Linguistic Theories (TLT), Barcelona, Spain, pp. 149–160.

    Google Scholar 

  • Quirk, C. and S. Corston-Oliver (2006). The impact of parse quality on syntactically-informed statistical machine translation. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, Sydney, Australia, pp. 62–69.

    Google Scholar 

  • Ratnaparkhi, A. (1997). A linear observed time statistical parser based on maximum entropy models. In Proceedings of the 2nd Conference on Empirical Methods in Natural Language Processing. Brown University, Providence, RI, pp. 1–10.

    Google Scholar 

  • Saetre, R., K. Sagae, and J. Tsujii (2007). Syntactic features for protein–protein interaction extraction. In Short Paper Proceedings of the 2nd International Symposium on Languages in Biology and Medicine, Biopolis, Singapore, pp. 6.1–6.14.

    Google Scholar 

  • Sagae, K. and A. Lavie (2006a). A best-first probabilistic shift-reduce parser. In Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics Main Conference Poster Session (COLING-ACL 2006), Syndey, Australia, pp. 691–698.

    Google Scholar 

  • Sagae, K. and A. Lavie (2006b). Parser combination by reparsing. In Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers, New York, NY, pp. 129–132.

    Google Scholar 

  • Tomita, M. (1987). An efficient augmented context-free parsing algorithm. Compuatational Linguist 31, 31–46.

    Google Scholar 

  • Tomita, M. (1990). The generalized lr parser/compiler – version 8.4. In Proceedings of the International Conference on Computational Linguistics (COLING’90), Helsinki, pp. 59–63.

    Google Scholar 

  • Vapnik, V.N. (1995). The Mature of Statistical Learning Theory. New York, NY: Springer.

    Google Scholar 

  • Wang, M., N.A. Smith, and T. Mitamura (2007). What is the jeopardy model? a quasisynchronous grammar for qa. In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLPCoNLL), Prague, Czech Republic, pp. 22–32.

    Google Scholar 

  • Yamada, H. and Y. Matsumoto (2003). Statistical dependency analysis with support vector machines. In Proceedings of the 8th International Workshop on Parsing Technologies (IWPT), Nancy, France, pp. 195–206.

    Google Scholar 

  • Zeman, D. and Žabokrtský, Z. (2005). Improving parsing accuracy by combining diverse dependency parsers. In Proceedings of the 9th International Workshop on Parsing Technologies (IWPT 2005), Vancouver, BC, pp. 171–178.

    Google Scholar 

Download references

Acknowledgements

We thank the shared task organizers and treebank providers. We also thank the CoNLL 2007 shared task reviewers for their comments and suggestions, and Yusuke Miyao for insightful discussions. This work was supported in part by Grant-in-Aid for Specially Promoted Research 18002007.

Author information

Authors and Affiliations

  1. Institute for Creative Technologies, University of Southern California, Marina del Rey, CA, 90292, USA

    Kenji Sagae

  2. Department of Computer Science, Faculty of Information Science and Technology, University of Tokyo, Tokyo, 113-0033, Japan

    Jun-ichi Tsujii

  3. School of Computer Science, University of Manchester, Manchester, UK

    Jun-ichi Tsujii

  4. National Center for Text Mining (NaCTeM), Manchester, UK

    Jun-ichi Tsujii

Authors
  1. Kenji Sagae
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jun-ichi Tsujii
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kenji Sagae .

Editor information

Editors and Affiliations

  1. Tilburg University, Warandelaan 2, Tilburg, 5000 LE, Netherlands

    Harry Bunt

  2. Dépt. Linguistique, Université de Genève, rue de Candolle 2, Genève, 1211, Switzerland

    Paola Merlo

  3. Pimpstensvägen 16, Uppsala, 752 67, Sweden

    Joakim Nivre

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Sagae, K., Tsujii, Ji. (2010). Dependency Parsing and Domain Adaptation with Data-Driven LR Models and Parser Ensembles. In: Bunt, H., Merlo, P., Nivre, J. (eds) Trends in Parsing Technology. Text, Speech and Language Technology, vol 43. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9352-3_4

Download citation

Publish with us

Policies and ethics

Search

Navigation