Abstract
This paper presents the process of enriching the verb frame database of a Hungarian natural language parser to enable the assignment of semantic roles. We accomplished this by linking the parser’s verb frame database to existing linguistic resources such as VerbNet and WordNet, and automatically transferring back semantic knowledge. We developed OWL ontologies that map the various constraint description formalisms of the linked resources and employed a logical reasoning device to facilitate the linking procedure. We present results and discuss the challenges and pitfalls that arose from this undertaking. We also compare our rule-based approach with that of using a state-of-the-art English semantic role labeler pipeline for the thematic role transferring task.
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Notes
- 1.
The whole system with pretrained models can be downloaded at https://github.com/microth/PathLSTM.
References
Palmer, M., Gildea, D., Xue, N.: Semantic role labeling. Synth. Lect. Hum. Lang. Technol. 3(1), 1–103 (2010)
Prószéky, G., Indig, B., Miháltz, M., Sass, B.: Egy pszicholingvisztikai indíttatású számítógépes nyelvfeldolgozási modell felé. In: XI. Magyar Számítógépes Nyelvészeti Konferencia, Szeged, 2014, pp. 79–87 (2014)
Sass, B.: Egy kereslet-kínálat elvű elemző működése és a koordináció kezelésének módszere. In: XI. Magyar Számítógépes Nyelvészeti Konferencia, Szeged, 2015, pp. 309–311 (2015)
Pléh, C.: Formal connexity and pragmatic cohesion in anaphora interpretation. In: Text and Discourse Connectedness. In: Proceedings of the Conference on Connexity and Coherance, Urbino, pp. 137–52 (1989)
Morrill, G.: Categorial Grammar: Logical Syntax, Semantics, and Processing. Oxford University Press, Oxford (2010)
Prószéky, G., Tihanyi, L.: MetaMorpho: a pattern-based machine translation system. In: Proceedings of the 24th Translating and the Computer Conference, pp. 19–24 (2002)
Prószéky, G., Indig, B.: Magyar szövegek pszicholingvisztikai indíttatású elemzése számítógéppel. Alkalmazott Nyelvtudomány XV(1–2), 29–44 (2015)
Schuler, K.K.: VerbNet: a broad-coverage, comprehensive verb lexicon. Ph.D. thesis, University of Pennsylvania (2005)
Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)
Haarslev, V., Hidde, K., Möller, R., Wessel, M.: The RacerPro knowledge representation and reasoning system. Semant. Web J. 3(3), 267–277 (2012)
Gildea, D., Jurafsky, D.: Automatic labeling of semantic roles. Comput. Linguist. 28(3), 245–288 (2002)
Carreras, X., Màrquez, L.: Introduction to the CoNLL-2005 shared task: semantic role labeling. In: Proceedings of the Ninth Conference on Computational Natural Language Learning, CoNLL 2005, pp. 152–164. ACL, Stroudsburg (2005)
Ku, L.W., Virk, S.M., Lee, Y.H.: A dual-layer semantic role labeling system. In: ACL-IJCNLP 2015, p. 49 (2015)
Loper, E., Yi, S.T., Palmer, M.: Combining lexical resources: mapping between PropBank and VerbNet. In: Proceedings of the 7th International Workshop on Computational Linguistics, Tilburg (2007)
Gurevych, I., Eckle-Kohler, J., Hartmann, S., Matuschek, M., Meyer, C.M., Wirth, C.: UBY - a large-scale unified lexical-semantic resource based on LMF. In: Proceedings of the 13th Conference of the European Chapter of the ACL (EACL 2012), pp. 580–590, April 2012
Navigli, R., Ponzetto, S.P.: BabelNet: the automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artif. Intell. 193, 217–250 (2012)
Schmachtenberg, M., Bizer, C., Jentzsch, A., Cyganiak, R.: Linking open data cloud diagram 2014 (2014). http://lod-cloud.net/
Levin, B.: English Verb Classes and Alternations: A Preliminary Investigation. University of Chicago Press, Chicago (1993)
Sass, B.: A unified method for extracting simple and multiword verbs with valence information. In: Proceedings of RANLP 2009, Borovec, Bulgaria, pp. 399–403 (2009)
Sass, B.: The verb argument browser. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds.) TSD 2008. LNCS (LNAI), vol. 5246, pp. 187–192. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-87391-4_25
Váradi, T.: The Hungarian National Corpus. In: Proceedings of the Second International Conference on Language Resources and Evaluation, Las Palmas, pp. 385–389 (2002)
Vossen, P., Bloksma, L., Rodriguez, H., Climent, S., Calzolari, N., Roventini, A., Bertagna, F., Alonge, A., Peters, W.: The EuroWordNet base concepts and top ontology. Technical report, EuroWordNet project (1998)
Liebig, T., Luther, M., Noppens, O., Wessel, M.: OWLlink. Semant. Web Interoper. Usability Appl. 2(1), 23–32 (2011)
Roth, M., Lapata, M.: Neural semantic role labeling with dependency path embeddings. In: Proceedings of ACL 2016, Berlin, pp. 1192–1202 (2016)
Roth, M., Lapata, M.: PathLSTM, GitHub repository (2017). https://github.com/microth/PathLSTM
Manning, C.D., Surdeanu, M., Bauer, J., Finkel, J.R., Bethard, S., McClosky, D.: The Stanford CoreNLP natural language processing toolkit. In: Proceedings of ACL 2014: System Demonstrations, pp. 55–60 (2014)
Bohnet, B.: Very high accuracy and fast dependency parsing is not a contradiction. In: Proceedings of the 23rd International Conference on Computational Linguistics, pp. 89–97. Association for Computational Linguistics (2010)
Björkelund, A., Hafdell, L., Nugues, P.: Multilingual semantic role labeling. In: Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task, pp. 43–48. Association for Computational Linguistics (2009)
Indig, B., Miháltz, M., Simonyi, A.: Exploiting linked linguistic resources for semantic role labeling. In: 7th Language and Technology Conference: Human Language Technologies as a Challenge for Computer Science and Linguistics, pp. 140–144. Uniwersytet im. Adama Mickiewicza w Poznaniu, Poznań (2015)
Indig, B., Miháltz, M., Simonyi, A.: Mapping ontologies using ontologies: Cross-lingual semantic role information transfer. In: Chair, N.C.C., Choukri, K., Declerck, T., Goggi, S., Grobelnik, M., Maegaard, B., Mariani, J., Mazo, H., Moreno, A., Odijk, J., Piperidis, S. (eds.) Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). European Language Resources Association (ELRA), Paris, pp. 2425–2430, May 2016
Acknowledgements
An earlier, shorter version of this paper, in which the evaluation was based on a substantially smaller gold standard and a smaller set of frames (excluding complements), was presented at the 7th Language & Technology Conference in Poznań in 2015 [29]. Another paper detailing the publicly available underlying ontology was presented at LREC 2016 in Protorož [30].
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Indig, B., Miháltz, M., Simonyi, A. (2018). Methods of Linking Linguistic Resources for Semantic Role Labeling. In: Vetulani, Z., Mariani, J., Kubis, M. (eds) Human Language Technology. Challenges for Computer Science and Linguistics. LTC 2015. Lecture Notes in Computer Science(), vol 10930. Springer, Cham. https://doi.org/10.1007/978-3-319-93782-3_14
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