Abstract
We introduce a system for anaphora resolution for German that uses various resources in order to develop a real system as opposed to systems based on idealized assumptions, e.g. the use of true mentions only or perfect parse trees and perfect morphology. The components that we use to replace such idealizations comprise a full-fledged morphology, a Wikipedia-based named entity recognition, a rule-based dependency parser and a German wordnet. We show that under these conditions coreference resolution is (at least for German) still far from being perfect.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Klenner, M., Ailloud, E.: Optimization in Coreference Resolution Is Not Needed: A Nearly-Optimal Zero-One ILP Algorithm with Intensional Constraints. In: Proceedings of the EACL (2009)
Hamp, B., Feldweg, H.: GermaNet—a Lexical-Semantic Net for German. In: Proc. of ACL Workshop Automatic Information Extraction and Building of Lexical Semantic Resources for NLP Applications (1997)
Daelemans, W., Zavrel, J., van der Sloot, K., van den Bosch, A.: TiMBL: Tilburg Memory-Based Learner (2004)
Schneider, G.: Hybrid Long-Distance Functional Dependency Parsing. Doctoral Thesis, Institute of Computational Linguistics, Univ. of Zurich (2008)
Telljohann, H., Hinrichs, E.W., Kübler, S.: The TüBa-D/Z Treebank: Annotating German with a Context-Free Backbone. In: Proc. of the Fourth Intern. Conf. on Language Resources and Evaluation, Lisbon, Portugal (2004)
Sennrich, R., Schneider, G., Volk, M., Warin, M.: A New Hybrid Dependency Parser for German. In: Proc. of the German Society for Computational Linguistics and Language Technology 2009 (GSCL 2009), Potsdam, Germany, pp. 115–124 (2009)
Naumann, K.: Manual for the Annotation of Indocument Referential Relations. Electronic document, (2006), http://www.sfs.uni-tuebingen.de/tuebadz.shtml
Soon, W., Ng, H., Lim, D.: A Machine Learning Approach to Coreference Resolution of Noun Phrases. Computational Linguistics 27(4), 521–544 (2001)
Versley, Y.: A Constraint-Based Approach to Noun Phrase Coreference Resolution in German Newspaper Text. In: Konferenz zur Verarbeitung Natürlicher Sprache, KONVENS (2006)
Hinrichs, E., Filippova, K., Wunsch, H.: A Data-driven Approach to Pronominal Anaphora Resolution in German. In: Proc. of RANLP (2005)
Wunsch, H., Kübler, S., Cantrell, R.: Instance Sampling Methods for Pronoun Resolution. In: Proc. of RANLP, Borovets, Bulgaria (2009)
Schiehlen, M.: Optimizing Algorithms for Pronoun Resolution. In: Proceed. of the 20th International Conference on Computational Linguistics (2004)
Klenner, M., Ailloud, E.: Enhancing Coreference Clustering. In: Johansson, C. (ed.) Proc. of the Second Workshop on Anaphora Resolution (WAR II), Bergen, Norway. NEALT Proceedings Series, vol. 2 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Klenner, M., Fahrni, A., Sennrich, R. (2010). Real Anaphora Resolution Is Hard. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2010. Lecture Notes in Computer Science(), vol 6231. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15760-8_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-15760-8_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15759-2
Online ISBN: 978-3-642-15760-8
eBook Packages: Computer ScienceComputer Science (R0)