Abstract
This paper presents a Lexicon-Grammar based method for automatic extraction of spatial relations from Italian non-structured data. We used the software Nooj to build sophisticated local grammars and electronic dictionaries associated with the lexicon-grammar classes of the Italian intransitive spatial verbs (i.e. 234 verbal entries) and we applied them to the Italian text Il Codice da Vinci (‘The Da Vinci Code’, by Dan Brown) in order to parse the spatial predicate-arguments structures. In addition, Nooj allowed us to automatically annotate (in XML format) the words (or the sequence of words) that in each sentence (S) of the text play the ‘spatial roles’ of Figure (F), Motion (M) and Ground (G). Finally the results of the experiment and the evaluation of this method will be discussed.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Russom, P.: Big data analytics. TDWI Best Practices Report, Fourth Quarter (2011)
McAfee, A., Brynjolfsson, E.: Big data: the management revolution. Harvard Business Review 90(10), 60–66 (2012)
Villars, R.L., Olofson, C.W., Eastwood, M.: Big data: What it is and why you should care. White Paper, IDC (2011)
Ganz, J., Reinsel, D.: Extracting value from chaos. In: Gunn, J. (s.d.) IDC, Libraries in Science Fiction (2011)
Amato, F., Mazzeo, A., Moscato, V., Picariello, A.: A system for semantic retrieval and long-term preservation of multimedia documents in the e-government domain. International Journal of Web and Grid Services 5(4), 323–338 (2009)
Amato, F., Mazzeo, A., Moscato, V., Picariello, A.: Exploiting cloud technologies and context information for recommending touristic paths. In: Zavoral, F., Jung, J.J., Badica, C. (eds.) Intelligent Distributed Computing VII. SCI, vol. 511, pp. 281–287. Springer, Heidelberg (2014)
Beavers, J., Wei, T.S., Levin, B.: The typology of motion expressions revisited. Journal of Linguistics 46, 331–377 (2009)
Bateman, J.A.: Language and space: a two-level semantic approach based on principles of ontological engineering. International Journal of Speech Technology 13(1), 29–48 (2010)
Li, H., Zhao, T., Li, S., Zhao, J.: The extraction of trajectories from real texts based on linear classification. In: Proceedings of NODALIDA 2007 Conference, pp. 121–127 (2007)
Kordjamshidi, P., Van Otterlo, M., Moens, M.: Spatial Role Labeling: Towards Extraction of Spatial Relations from Natural Language. ACM Journal 5 (2011)
Bocchino, F.: Lessico-Grammatica dell’Italiano: le costruzioni intransitive. Ph.D Thesis in General Linguistics, University of Salerno (2006)
Palmer, M., Gildea, D., Xue, N.: Semantic Role Labeling. Morgan and Claypool (2010)
Baptista, J., Talhadas, R., Mamede, N.: Semantic Roles for Portuguese Verbs. In: Proceedings of the 32nd Conference on Lexis and Grammar, Faro, September 10-14, University of Algarve, Portugal (2013)
Palmer, M., Gildea, D., Kingsbury, P.: The proposition bank: An annotated corpus of semantic roles. Computational Linguistics 31(1), 71–106 (2005)
Rahimi Rastgar, S., Razavi, N.: A System for Building Corpus Annotated With Semantic Roles. Doctoral dissertation, Jönköping University (2013)
Monachesi, P.: Annotation of semantic role. Utrechet University, Netherlands (2009)
Ruppenhofer, J., Ellsworth, M., Petruck, M.R., Johnson, C.R., Scheffczyk, J.: FrameNet II: Extended theory and practice (2006)
Basili, R., De Cao, D., Lenci, A., Moschitti, A., Venturi, G.: Evalita 2011: the frame labeling over italian texts task. In: Evaluation of Natural Language and Speech Tools for Italian, pp. 195–204 (2013)
Giuglea, A.M., Moschitti, A.: Semantic role labeling via framenet, verbnet and propbank. In: Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics, pp. 929–936 (2006)
Gross, M.: Les bases empiriques de la notion de prédicat sémantique. In: Langages, Larousse, Paris, vol. (63) (1981)
Elia, A.: On lexical, semantic and syntactic granularity of Italian verbs. In: Kakoyianni - Doa, F. (ed.) Penser le Lexique Grammaire: Perspectives Actuelles, Honoré Champion, Paris, pp. 277–286 (2013)
Elia, A., Vietri, S., Postiglione, A., Monteleone, M., Marano, F.: Data Mining Modular Software System. In: Proceedings of SWWS 2010 – The International Conference on Semantic Web and Web Service, Las Vegas, Nevada, USA (2010)
Vietri, S.: The Construction of an Annotated Corpus for the Analysis of Italian Transfer Predicates. In: Linguisticae Investigationes. Benjamins, Amsterdam (2013)
Talmy: Toward a Cognitive Semantics. Typology and process in concept structuring vol. II. The MIT Press, Cambridge (2000)
Silberztein, M.: Nooj manual (2003), http://www.nooj.com
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Elia, A., Guglielmo, D., Maisto, A., Pelosi, S. (2013). A Linguistic-Based Method for Automatically Extracting Spatial Relations from Large Non-Structured Data. In: Aversa, R., Kołodziej, J., Zhang, J., Amato, F., Fortino, G. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2013. Lecture Notes in Computer Science, vol 8286. Springer, Cham. https://doi.org/10.1007/978-3-319-03889-6_22
Download citation
DOI: https://doi.org/10.1007/978-3-319-03889-6_22
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03888-9
Online ISBN: 978-3-319-03889-6
eBook Packages: Computer ScienceComputer Science (R0)