Learning context-free grammars to extract relations from text

Frontiers in Artificial Intelligence and Applications

Volumn 178, Issue , 2008, Pages 303-307

  Petasis, Georgios ^a   Karkaletsis, Vangelis ^a   Paliouras, Georgios ^a   Spyropoulos, Constantine D ^a  

^a INSTITUTE OF NANOSCIENCE AND NANOTECHNOLOGY   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; SUPERVISED LEARNING;

CONTEXT-FREE GRAMMARS; EXTRACTION METHOD; GRAMMAR LEARNING; GRAMMATICAL INFERENCES; LEARNING CONTEXT; NAMED ENTITIES; POSITIVE EXAMPLES; RELATION EXTRACTION; SEMI-SUPERVISED LEARNING; SUPERVISED LEARNING APPROACHES;

CONTEXT FREE GRAMMARS;

EID: 79955862470     PISSN: 09226389     EISSN: 18798314     Source Type: Book Series    
DOI: 10.3233/978-1-58603-891-5-303     Document Type: Conference Paper

References (21)

1. th Message Understanding Conference (MUC-7), April, 1998. http://www-nlpir.nist.gov/related_projects/muc/proceedings/muc_7_toc.html
2. CoNLL, 2008: http://www.yr-bcn.es/conll2008/
3. Carreras X. and Màrquez L., “Introduction to the CoNLL-2005 Shared Task: Semantic Role Labeling”, In Proc. of the Ninth Conference on Natural Language Learning (CoNLL-2005), June 29 – 30, Michigan, USA, 2005. http://www.lsi.upc.edu/~esrlconll/st05/st05.html
4. Carreras X. and Màrquez L., “Introduction to the CoNLL-2004 Shared Task: Semantic Role Labeling”, In Proc. of the Eighth Conference on Natural Language Learning (CoNLL-2004), Workshop of HLT/NAACL 2004, May 6 – 7, Boston, MA, USA, 2004. http://www.lsi.upc.edu/~srlconll/st04/st04.html
5. Hearst M., “Automatic acquisition of hyponyms from large text corpora”, In Proc. of the 14th International Conference on Computational Linguistics (COLING-1992), 1992.
6. Davidov D., Rappoport A., and Koppel M., “Fully Unsupervised Discovery of Concept-Specific Relationships by Web Mining”, In Proc. of the 45th Annual Meeting of the Association of Computational Linguistics, pp. 232 – 239, Prague, Czech Republic, June, 2007. http://www.aclweb.org/anthology/P/P07/P07-1030
7. Brody S., “Clustering Clauses for High-Level Relation Detection: An Information-theoretic Approach”, In Proc. of the 45th Annual Meeting of the Association of Computational Linguistics, pp. 448 – 455, Prague, Czech Republic, June, 2007. http://www.aclweb.org/anthology/P/P07/P07-1057
8. Bunescu R., and Mooney R., “Learning to Extract Relations from the Web using Minimal Supervision”, In Proc. of the 45th Annual Meeting of the Association of Computational Linguistics, pp. 576 – 583, Prague, Czech Republic, June, 2007. http://www.aclweb.org/anthology/P/P07/P07-1073
9. Xu F., Uszkoreit H., Li H., “A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity”, In Proc. of the 45th Annual Meeting of the Association of Computational Linguistics, pp. 584 – 591, Prague, Czech Republic, June, 2007. http://www.aclweb.org/anthology/P/P07/P07-1074
10. Rosenfeld B., and Feldman R., “Using Corpus Statistics on Entities to Improve Semi-supervised Relation Extraction from the Web”, In Proc. of the 45th Annual Meeting of the Association of Computational Linguistics, pp. 600 – 607, Prague, Czech Republic, June, 2007. http://www.aclweb.org/anthology/P/P07/P07-1076
11. Petasis G., Paliouras G., Spyropoulos C. D. and Halatsis C., “eg-GRIDS: Context-Free Grammatical Inference from Positive Examples using Genetic Search”. In Proc. of the 7th International Colloquium on Grammatical Inference (ICGI 2004), Lecture Notes in Artificial Intelligence 3264, pp. 223 – 234, Springer, 2004.
12. Petasis G., Paliouras G., Karkaletsis V., Halatsis C., and Spyropoulos C. D., “e-GRIDS: Computationally Efficient Grammatical Inference from Positive Examples”. GRAMMARS, (7), pp. 69 – 110, 2004. (http://grammars.grlmc.com/special.asp)
13. Rissanen J., “Stochastic Complexity in Statistical Inquiry”, World Scientific Publishing Co, Singapore, 1989.
14. Pustejovsky J., Castano J., Zhang J., Cochran B., and Kotecki M., “Robust relational parsing over biomedical literature: Extracting inhibit relations” In Pacific Symposium on Biocomputing, 2002. http://citeseer.ist.psu.edu/527763.html
15. Leroy G. and Chen H., “Genescene: An Ontology-enhanced Integration of Linguistic and Co-occurrence based Relations in Biomedical Texts” In Journal of the American Society for Information Systems and Technology (JASIST), 56 (5), 457 – 468, March 2005. http://beta.cgu.edu/Faculty/leroyg/Leroy-JASIST-2005.pdf
16. th International Joint Conference on Artificial Intelligence (IJCAI 2001), 2001.
17. Ciravegna F., and Lavelli A., “LearningPinocchio: Adaptive Information Extraction for Real World Applications”, In Journal of Natural Language Engineering, 10 (2), 2004.
18. th International Colloquium on Grammatical Inference (ICGI 2004), vol. 3264 of LNCS/LNAI, pp. 16 – 27, Springer-Verlag, 2004.
19. Katrenko S., and Adriaans P., “Learning Relations from Biomedical Corpora Using Dependency Tree Levels”, In Proceedings of the Fifteenth Dutch-Belgian Conference on Machine Learning (Benelearn), Ghent, Belgium, May 12, 2006. http://staff.science.uva.nl/~katrenko/katrenko_adriaans.pdf
20. http://boost-sandbox.sourceforge.net/libs/xpressive/doc/html/index.html
21. Lafferty J., McCallum A., and Pereira F., “Conditional random fields: Probabilistic models for segmenting and labeling sequence data”, In Proc. of ICML, pp.282 – 289, 2001.