Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-24T04:34:14.596Z Has data issue: false hasContentIssue false
  • English
  • Français

Improving mention detection for Basque based on a deep error analysis

Published online by Cambridge University Press:  12 July 2016

ANDER SORALUZE ,
OLATZ ARREGI ,
XABIER ARREGI  and
ARANTZA DÍAZ DE ILARRAZA
ANDER SORALUZE
Affiliation:
IXA Group, University of the Basque Country, Donostia-San Sebastián, Spain. e-mails [email protected], [email protected], [email protected], [email protected].
OLATZ ARREGI
Affiliation:
IXA Group, University of the Basque Country, Donostia-San Sebastián, Spain. e-mails [email protected], [email protected], [email protected], [email protected].
XABIER ARREGI
Affiliation:
IXA Group, University of the Basque Country, Donostia-San Sebastián, Spain. e-mails [email protected], [email protected], [email protected], [email protected].
ARANTZA DÍAZ DE ILARRAZA
Affiliation:
IXA Group, University of the Basque Country, Donostia-San Sebastián, Spain. e-mails [email protected], [email protected], [email protected], [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper presents the improvement process of a mention detector for Basque. The system is rule-based and takes into account the characteristics of mentions in Basque. A classification of error types is proposed based on the errors that occur during mention detection. A deep error analysis distinguishing error types and causes is presented and improvements are proposed. At the final stage, the system obtains an F-measure of 74.57% under the Exact Matching protocol and of 80.57% under Lenient Matching. We also show the performance of the mention detector with gold standard data as input, in order to omit errors caused by the previous stages of linguistic processing. In this scenario, we obtain an F-measure of 85.89% with Strict Matching and of 89.06% with Lenient Matching, i.e., a difference of 11.32 and 8.49 percentage points, respectively. Finally, how improvements in mention detection affect coreference resolution is analysed.

Type
Articles
Information
Natural Language Engineering , Volume 23 , Issue 3 , May 2017 , pp. 351 - 384
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aduriz, I., Aranzabe, M., Arriola, J. M., Atutxa, M., Díaz de Ilarraza, A., Ezeiza, N., Gojenola, K., Oronoz, M., Soroa, A., and Urizar, R., 2006. Methodology and steps towards the construction of EPEC, a corpus of written Basque tagged at morphological and syntactic levels for the automatic processing. Language and Computers 56 (1): 1–15.Google Scholar
Aduriz, I., and Díaz de Ilarraza, A. 2003. Morphosyntactic disambiguation and shallow parsing in computational processing of Basque. In Oyharçabal, B. (ed.), Inquiries into the lexicon-syntax relations in Basque, pp. 1–21. University of the Basque Country, Bilbao, Spain.Google Scholar
Alegria, I., Ansa, O., Artola, X., Ezeiza, N., Gojenola, K., and Urizar, R., 2004. Representation and treatment of multiword expressions in Basque. In ACL Workshop on Multiword Expressions (MWE ’04), Barcelona, Spain, pp. 48–55.Google Scholar
Alegria, I., Aranzabe, M., Ezeiza, N., Ezeiza, A., and Urizar, R. 2002. Using finite state technology in natural language processing of Basque. In Watson, B. W., and Wood, D. Implementation and Application of Automata, pp. 1–12. Lecture Notes in Computer Science. Berlin: Springer/Heidelberg.Google Scholar
Alegria, I., Artola, X., Sarasola, K., and Urkia, M., 1996. Automatic morphological analysis of Basque. Literary & Linguistic Computing 11 (4): 193–203.CrossRefGoogle Scholar
Alegria, I., Ezeiza, N., Fernandez, I., and Urizar, R., 2003. Named entity recognition and classification for texts in Basque. In II Jornadas de Tratamiento y Recuperación de Información (JOTRI 2003), Madrid, Spain, pp. 198–203.Google Scholar
Arrieta, B. 2010. Azaleko sintaxiaren tratamendua ikasketa automatikoko tekniken bidez: euskarako kateen eta perpausen identifikazioa eta bere erabilera koma-zuzentzaile batean. PhD Thesis, Computer Languages and Systems, University of the Basque Country, Donostia-San Sebastián, Spain.Google Scholar
Artstein, R., and Poesio, M., 2008. Inter-coder agreement for computational linguistics. Computational Linguistics 34 (4): 555–96.Google Scholar
Bagga, B., and Badlwin, B., 1998. Algorithms for scoring coreference chains. In Proceedings of the 1st International Conference on Language Resources and Evaluation Workshop on Linguistics Coreference, Granada, Spain, pp. 563–66.Google Scholar
Broscheit, S., Poesio, M., Ponzetto, S. P., Rodriguez, K. J., Romano, L., Uryupina, O., Versley, Y., and Zanoli, R., 2010. BART: a multilingual anaphora resolution system. In Proceedings of the 5th International Workshop on Semantic Evaluation (SemEval 2010), Uppsala, Sweden, pp. 104–07.Google Scholar
Chang, K.-W., Samdani, R., Rozovskaya, A., Rizzolo, N., Sammons, M., and Roth, D., 2011. Inference protocols for coreference resolution. In Proceedings of the 15th Conference on Computational Natural Language Learning: Shared Task (CoNLL 2011), Portland, Oregon, pp. 40–4.Google Scholar
Doddington, G., Mitchell, A., Przybocki, M., Ramshaw, L., Strassel, S., and Weischedel, R., 2004. The automatic content extraction (ACE) program–tasks, data, and evaluation. In Proceedings of Language Resources and Evaluation Conference (LREC 2004), Lisbon, Portugal, pp. 837–40.Google Scholar
Hacioglu, K., Douglas, B., and Chen, Y., 2005. Detection of entity mentions occuring in english and Chinese text. In Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing (HLT ’05), Vancouver, British Columbia, Canada, pp. 379–86.Google Scholar
Hulden, M., 2009. Foma: a finite-state compiler and library. In Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2009), Athens, Greece, pp. 29–32.Google Scholar
Karlsson, F., Voutilainen, J., Heikkilä, J., and Anttila, A., 1995. Constraint Grammar: Language-independent System for Parsing Unrestricted Text. Berlin: Mouton de Gruyter.CrossRefGoogle Scholar
Klein, D., and Manning, C., 2003. Accurate unlexicalized parsing. In Proceedings of the 41st Annual Meeting on Association for Computational Linguistics (ACL ’03), Sapporo, Japan, pp. 423–30.Google Scholar
Kopeć, M., and Ogrodniczuk, M. 2014. Inter-annotator agreement in coreference annotation of Polish. In Sobecki, J., Boonjing, V., and Chittayasothorn, S., (eds.), Advanced Approaches to Intelligent Information and Database Systems, Studies in Computational Intelligence, vol. 551. Switzerland: Springer. Springer International Publishing, Switzerland.Google Scholar
Kummerfeld, J. K., Bansal, M., Burkett, D., and Klein, D., 2011. Mention detection: heuristics for the OntoNotes annotations. In Proceedings of the 15th Conference on Computational Natural Language Learning: Shared Task (CoNLL 2011), Portland, Oregon, pp. 102–6.Google Scholar
Kummerfeld, J. K., and Klein, D., 2011. Error-driven analysis of challenges in coreference resolution. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), Seattle, Washington, USA, pp. 265–77.Google Scholar
Laka, I. 1996. A brief grammar of Euskara, the Basque language. http://www.ehu.es/grammar. University of the Basque Country.Google Scholar
Lalitha, D. S., Sundar, R. V., and Rao, R. K. P., 2014. A generic anaphora resolution engine for Indian languages. In Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers, Dublin, Ireland, pp. 1824–33.Google Scholar
Lee, H., Chang, A., Peirsman, Y., Chambers, N., Surdeanu, M., and Jurafsky, D., 2013. A generic anaphora resolution engine for Indian languages. Computational Linguistics 39 (4): 885–916.Google Scholar
Luo, X., 2005. On coreference resolution performance metrics. In Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing (HLT ’05), Vancouver, British Columbia, Canada, pp. 25–32.Google Scholar
Marcus, M., Marcinkiewicz, M., and Santorini, B., 1993. Building a large annotated corpus of english: the Penn treebank. Computational Linguistics 19 (2): 313–30.Google Scholar
Màrquez, L., Recasens, M., and Sapena, E., 2013. Coreference resolution: an empirical study based on SemEval-2010 shared task 1. Language Resources and Evaluation 47 (3): 661–94.CrossRefGoogle Scholar
Miháltz, M. 2008. Knowledge-based coreference resolution for Hungarian. In Proceedings of the 6th International Conference on Language Resources and Evaluation (LREC’08), Marrakech, Morocco.Google Scholar
MUC-6, 1995. Coreference Task Definition (v2.3, 8 Sep 95). In Proceedings of the 6th Message Understanding Conference (MUC-6), Columbia, Maryland, USA, pp. 335–44.Google Scholar
MUC-7 1998. Coreference task definition (v3.0, 13 Jul 97). In Proceedings of the 7th Message Understanding Conference (MUC-7), Fairfax, Virginia, USA.Google Scholar
NIST 2008. Automatic Content Extraction 2008 Evaluation Plan (ACE08).Google Scholar
Ngụy, G., Novák, V., and Żabokrtský, Z., 2009. Comparison of classification and ranking approaches to pronominal anaphora resolution in Czech. In Proceedings of the SIGDIAL 2009 Conference, London, UK, pp. 276–85.Google Scholar
Nguyen, N., Kim, J.-D., and Tsujii, J., 2008. Challenges in pronoun resolution system for biomedical text. In Proceedings of the International Conference on Language Resources and Evaluation (LREC 2008), Marrakech, Morocco, pp. 2408–12.Google Scholar
Ogrodniczuk, M., and Kopeć, M. 2011. End-to-end coreference resolution baseline System for Polish. In Vetulani, Z. (ed.), Proceedings of the 5th Language & Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics, Oznań, Poland, pp. 167–71.Google Scholar
Ohta, T., Pyysalo, S., Tsujii, J., and Ananiadou, S., 2008. Open-domain anatomical entity mention detection. In Proceedings of the Workshop on Detecting Structure in Scholarly Discourse (ACL’12), Jeju, Republic of Korea, pp. 27–36.Google Scholar
Orasan, C., Cristea, D., Mitkov, R., and Branco, A. 2008. Anaphora resolution exercise: an overview. In Proceedings of the 6th International Conference on Language Resources and Evaluation (LREC’08), Marrakech, Morocco.Google Scholar
Pradhan, S., Hovy, E., Marcus, M., Palmer, M., Ramshaw, L., and Weischedel, R., 2007. OntoNotes: a unified relational semantic representation. In Proceedings of the International Conference on Semantic Computing (ICSC 2007), Irvine, California, pp. 517–26.Google Scholar
Pradhan, S., Moschitti, A., Xue, N., Uryupina, O., and Zhang, Y., 2012. CoNLL-2012 Shared task: modeling multilingual unrestricted coreference in OntoNotes. In Proceedings of the 16th Conference on Computational Natural Language Learning (CoNLL 2012), Jeju, Korea, pp. 1–40.Google Scholar
Pradhan, S., Ramshaw, L., Marcus, M., Palmer, M., Weischedel, R., and Xue, N., 2011. CoNLL-2011 shared task: modeling unrestricted coreference in OntoNotes. In Proceedings of the 15th Conference on Computational Natural Language Learning: Shared Task (CoNLL 2011), Portland, Oregon, pp. 1–27.Google Scholar
Pradhan, S., Luo, X., Recasens, M., Hovy, E., Ng, V., and Strube, V., 2014. Scoring coreference partitions of predicted mentions: A reference implementation. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014), Baltimore, Maryland, pp. 30–5.Google Scholar
Recasens, M., and Hovy, E., 2010. Coreference resolution across Corpora: languages, coding Schemes, and preprocessing information. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL ’10), Sweden, pp. 1423–32.Google Scholar
Recasens, M., and Hovy, M., 2011. BLANC: implementing the Rand index for coreference evaluation. Natural Language Engineering 17 (4): 485–510.Google Scholar
Recasens, M., Màrquez, L., Sapena, E., Martí, M. A., Taulé, M., Hoste, V., Poesio, M., and Versley, Y., 2010. SemEval-2010 task 1: coreference resolution in multiple languages. In Proceedings of the 5th International Workshop on Semantic Evaluation (SemEval 2010), Uppsala, Sweden, pp. 1–8.Google Scholar
Recasens, M., and Martí, M., 2010. AnCora-CO: coreferentially annotated corpora for Spanish and Catalan. Language Resources and Evaluation 44 (4): 315–45.Google Scholar
Soon, W. M., Ng, H. T., and Lim, D. C. Y., 2001. A machine learning approach to coreference resolution of noun phrases. Computational Linguistics 27 (4): 521–44.Google Scholar
Soraluze, A., Arregi, O., Arregi, X., Ceberio, K., and Díaz de Ilarraza, A., 2012. Mention detection: first steps in the development of a Basque correference resolution system. In KONVENS 2012, The 11th Conference on Natural Language Processing, Vienna, Austria, pp. 128–36.Google Scholar
Stoyanov, V., Gilbert, N., Cardie, C., and Riloff, E., 2009. Conundrums in noun phrase coreference resolution: making sense of the state-of-the-art. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, Suntec, Singapore, pp. 656–64.Google Scholar
Uryupina, O. 2008. Error analysis for learning-based coreference resolution. In Proceedings of the 6th International Conference on Language Resources and Evaluation (LREC 2008), Marrakech, Morocco.Google Scholar
Uryupina, O., 2010. Corry: a system for coreference resolution. In Proceedings of the 5th International Workshop on Semantic Evaluation (SemEval 2010), Uppsala, Sweden, pp. 100–3.Google Scholar
Uryupina, O., and Moschitti, A., 2013. Multilingual mention detection for coreference resolution. In Proceedings of the 6th International Joint Conference on Natural Language Processing, Nagoya, Japan, pp. 100–8.Google Scholar
Vilain, M., Burger, J., Aberdeen, J., Connolly, D., and Hirschman, L., 1995. A model-theoretic coreference scoring scheme. In Proceedings of the 6th Conference on Message Understanding (MUC6), Columbia, Maryland, pp. 45–52.Google Scholar
Versley, Y., Ponzetto, S. P., Poesio, M., Eidelman, V., Jern, A., Smith, J., Yang, X., and Moschitti, A., 2008. BART: a modular toolkit for coreference resolution. In Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies, Columbus, Ohio, pp. 9–12.Google Scholar
Zhekova, D., and Kübler, S., 2010. UBIU: a language-independent system for coreference resolution. In Proceedings of the 5th International Workshop on Semantic Evaluation (SemEval 2010), Uppsala, Sweden, pp. 96–9.Google Scholar