Semantic Role Labeling With Relative Clauses

Öz

One of the main goals of computerized linguistic studies is automatically finding the elements of a sentence. Separation of sentences with too many judgements into their elements is a more complicated process when compared with simple sentences. In this study, instead of separating the whole sentence into its elements, the separation of sub clauses into their own elements is suggested. This approach can be considered as dividing a hard problem into sub parts; and this had higher rate of achievement when compared with dividing the whole sentence into its elements. Condition Random Fields (CRF) algorithm was used for dividing the sentences automatically into subclauses and finding its elements.

Anahtar Kelimeler

• Natural Language Processing, Semantic Role Labeling, Condition Random Fields

Kaynakça

1. Turkish Source Site, Sentences according to structure, (2015, 10
2. June), Retrieved from: http://www.turkcesinifi.com/yapilarin a-gore-cumleler-t781.html Özköse, C., Amasyalı, M.F., "Common sense Knowledge Acquisition by Sentence Analysis ", Turkey IT Foundation, Computer Science and Engineering Journal, December 2012, 6.
3. Coşkun,N., “Finding constituents of Turkish sentences", Master Thesis, Istanbul Technical University, Science Institute, 2013.
4. Aygül, M., Karaalioğlu, G., Amasyalı, M.F. , " Prediction of Function Tags of the Simple Turkish Sentences by Condition Random Fields", Sigma- YTU Journal of Engineering and Natural Sciences,2014, 32(1),pp 23
5. Zafer, H.R., "Türki Diller İçin Uyarlanabilir Sözdizimsel Ayrıştırıcı", Master Thesis, Fatih Science Institute, 2011.
6. Sutton, C., McCallum,A., “An Introduction to Conditional Random Fields”, Foundations and Trends in Machine Learning,2011, 4 (4),pp 267
7. Şeker, G.A., Eryiğit, G., “Initial explorations on using CRFs for Turkish Named Recognition”, 24th International Conference on Computational Linguistics, COLING 2012, Mumbai, India, 2012. University, Entity
8. Özkaya, S., Diri, B., “Named Entity Recognition by Conditional Random Fields from Turkish informal texts”, Signal Processing and Communications Applications (SIU),Antalya,2011.

9. Singla, K., Tammewar, A., Jain, N. , Jain, S. ," Two-stage Approach for Hindi Dependency Parsing Using MaltParser", Workshop on Machine Translation and Parsing in Indian Languages, Mumbai, 2012.
10. Lafferty, J., McCallum, A., Pereira,F., "Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data International Conference on Machine Learning (ICML), San Francisco, Turkish Source Site, Sentences according to structure, (2015, 10
11. June), Retrieved from: http://www.turkcesinifi.com/yapilarin a-gore-cumleler-t781.html Özköse, C., Amasyalı, M.F., "Common sense Knowledge Acquisition by Sentence Analysis ", Turkey IT Foundation, Computer Science and Engineering Journal, December 2012, 6.
12. Coşkun,N., “Finding constituents of Turkish sentences", Master Thesis, Istanbul Technical University, Science Institute, 2013.
13. Aygül, M., Karaalioğlu, G., Amasyalı, M.F. , " Prediction of Function Tags of the Simple Turkish Sentences by Condition Random Fields", Sigma- YTU Journal of Engineering and Natural Sciences,2014, 32(1),pp 23
14. Zafer, H.R., "Türki Diller İçin Uyarlanabilir Sözdizimsel Ayrıştırıcı", Master Thesis, Fatih Science Institute, 2011.
15. Sutton, C., McCallum,A., “An Introduction to Conditional Random Fields”, Foundations and Trends in Machine Learning,2011, 4 (4),pp 267
16. Şeker, G.A., Eryiğit, G., “Initial explorations on using CRFs for Turkish Named Recognition”, 24th International Conference on Computational Linguistics, COLING 2012, Mumbai, India, 2012. University, Entity
17. Özkaya, S., Diri, B., “Named Entity Recognition by Conditional Random Fields from Turkish informal texts”, Signal Processing and Communications Applications (SIU),Antalya,2011.
18. Singla, K., Tammewar, A., Jain, N. , Jain, S. ," Two-stage Approach for Hindi Dependency Parsing Using MaltParser", Workshop on Machine Translation and Parsing in Indian Languages, Mumbai, 2012.
19. Lafferty, J., McCallum, A., Pereira,F., "Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data International Conference on Machine Learning (ICML), San Francisco,