article

Frame-semantic parsing

Authors:

André F. T. Martins,

Nathan Schneider,

Noah A. SmithAuthors Info & Claims

Computational Linguistics, Volume 40, Issue 1

Pages 9 - 56

https://doi.org/10.1162/COLI_a_00163

Published: 01 March 2014 Publication History

Abstract

Frame semantics is a linguistic theory that has been instantiated for English in the FrameNet lexicon. We solve the problem of frame-semantic parsing using a two-stage statistical model that takes lexical targets i.e., content words and phrases in their sentential contexts and predicts frame-semantic structures. Given a target in context, the first stage disambiguates it to a semantic frame. This model uses latent variables and semi-supervised learning to improve frame disambiguation for targets unseen at training time. The second stage finds the target's locally expressed semantic arguments. At inference time, a fast exact dual decomposition algorithm collectively predicts all the arguments of a frame at once in order to respect declaratively stated linguistic constraints, resulting in qualitatively better structures than nave local predictors. Both components are feature-based and discriminatively trained on a small set of annotated frame-semantic parses. On the SemEval 2007 benchmark data set, the approach, along with a heuristic identifier of frame-evoking targets, outperforms the prior state of the art by significant margins. Additionally, we present experiments on the much larger FrameNet 1.5 data set. We have released our frame-semantic parser as open-source software.

References

[1]

Auli, Michael and Adam Lopez. 2011. A comparison of loopy belief propagation and dual decomposition for integrated CCG supertagging and parsing. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 470-480, Portland, OR.

Digital Library

[2]

Baker, Collin, Michael Ellsworth, and Katrin Erk. 2007. SemEval-2007 task 19: Frame semantic structure extraction. In Proceedings of the Fourth International Workshop on Semantic Evaluations, pages 99-104, Prague.

Digital Library

[3]

Baluja, Shumeet, Rohan Seth, D. Sivakumar, Yushi Jing, Jay Yagnik, Shankar Kumar, Deepak Ravichandran, and Mohamed Aly. 2008. Video suggestion and discovery for YouTube: taking random walks through the view graph. In Proceedings of the 17th International Conference on the World Wide Web, pages 895-904, Beijing.

Digital Library

[4]

Bauer, Daniel and Owen Rambow. 2011. Increasing coverage of syntactic subcategorization patterns in FrameNet using VerbNet. In Proceedings of the 2011 IEEE Fifth International Conference on Semantic Computing, pages 181-184, Washington, DC.

Digital Library

[5]

Bejan, Cosmin A. 2009. Learning Event Structures From Text. Ph.D. thesis, The University of Texas at Dallas.

[6]

Bengio, Yoshua, Olivier Delalleau, and Nicolas Le Roux. 2006. Label propagation and quadratic criterion. In Olivier Chapelle, Bernhard Schölkopf, and Alexander Zien, editors, Semi-Supervised Learning. MIT Press, Cambridge, MA, pages 193-216.

[7]

Boas, Hans C. 2002. Bilingual FrameNet dictionaries for machine translation. In Proceedings of the Third International Conference on Language Resources and Evaluation, pages 1,364-1,371, Las Palmas.

[8]

Bottou, Léon. 2004. Stochastic learning. In Olivier Bousquet and Ulrike von Luxburg, editors, Advanced Lectures on Machine Learning, Lecture Notes in Artificial Intelligence, LNAI 3176. Springer Verlag, Berlin, pages 146-168.

[9]

Burbea, Jacob and Calyampudi R. Rao. 2006. On the convexity of some divergence measures based on entropy functions. IEEE Transactions on Information Theory, 28(3):489-495.

Digital Library

[10]

Burchardt, Aljoscha, Katrin Erk, and Anette Frank. 2005. A WordNet detour to FrameNet. In Bernhard Fisseni, Hans-Christian Schmitz, Bernhard Schröder, and Petra Wagner, editors, Sprachtechnologie, mobile Kommunikation und linguistische Resourcen, volume 8 of Computer Studies in Language and Speech. Peter Lang, Frankfurt am Main, pages 408-421.

[11]

Burchardt, Aljoscha and Anette Frank. 2006. Approaching textual entailment with LFG and FrameNet frames. In Proceedings of the Second PASCAL RTE Challenge Workshop, pages 92-97, Venice.

[12]

Burchardt, Aljoscha, Marco Pennacchiotti, Stefan Thater, and Manfred Pinkal. 2009. Assessing the impact of frame semantics on textual entailment. Natural Language Engineering, 15(4):527-550.

Digital Library

[13]

Carreras, Xavier and Lluís Màrquez. 2004. Introduction to the CoNLL-2004 shared task: Semantic role labeling. In Proceedings of the Eighth Conference on Computational Natural Language Learning, pages 89-97, Boston, MA.

[14]

Carreras, Xavier and Lluís Màrquez. 2005. Introduction to the CoNLL-2005 shared task: Semantic role labeling. In Proceedings of the Ninth Conference on Computational Natural Language Learning, pages 152-164, Ann Arbor, MI.

Digital Library

[15]

Chang, Yin-Wen and Michael Collins. 2011. Exact decoding of phrase-based translation models through Lagrangian relaxation. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pages 26-37, Edinburgh.

Digital Library

[16]

Chapelle, Olivier, Bernhard Schölkopf, and Alexander Zien, editors. 2006. Semi-Supervised Learning. MIT Press, Cambridge, MA.

[17]

Chen, Desai, Nathan Schneider, Dipanjan Das, and Noah A. Smith. 2010. SEMAFOR: Frame argument resolution with log-linear models. In Proceedings of the 5th International Workshop on Semantic Evaluation, pages 264-267, Upssala.

Digital Library

[18]

Corduneanu, Adrian and Tommi Jaakkola. 2003. On information regularization. In Proceedings of the Nineteenth Conference on Uncertainty in Artificial Intelligence, pages 151-158, Acapulco.

Digital Library

[19]

Das, Dipanjan, André F. T. Martins, and Noah A. Smith. 2012. An exact dual decomposition algorithm for shallow semantic parsing with constraints. In Proceedings of the First Joint Conference on Lexical and Computational Semantics, pages 209-217, Montréal.

Digital Library

[20]

Das, Dipanjan and Slav Petrov. 2011. Unsupervised part-of-speech tagging with bilingual graph-based projections. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 600-609, Portland, OR.

Digital Library

[21]

Das, Dipanjan, Nathan Schneider, Desai Chen, and Noah A. Smith. 2010. Probabilistic frame-semantic parsing. In Proceedings of the Human Language Technologies Conference of the North American Chapter of the Association for Computational Linguistics, pages 948-956, Los Angeles, CA.

Digital Library

[22]

Das, Dipanjan and Noah A. Smith. 2011. Semi-supervised frame-semantic parsing for unknown predicates. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 1,435-1,444, Portland, OR.

Digital Library

[23]

Das, Dipanjan and Noah A. Smith. 2012. Graph-based lexicon expansion with sparsity-inducing penalties. In Proceedings of the Human Language Technologies Conference of the North American Chapter of the Association for Computational Linguistics, pages 677-687, Montréal.

Digital Library

[24]

Dean, Jeffrey and Sanjay Ghemawat. 2008. MapReduce: Simplified data processing on large clusters. Communications of the ACM, 51(1):107-113.

Digital Library

[25]

DeNero, John and Klaus Macherey. 2011. Model-based aligner combination using dual decomposition. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 420-429, Portland, OR.

Digital Library

[26]

Deschacht, Koen and Marie-Francine Moens. 2009. Semi-supervised semantic role labeling using the LatentWords Language Model. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, pages 21-29, Singapore.

Digital Library

[27]

Dhillon, Paramveer S., Partha Pratim Talukdar, and Koby Crammer. 2010. Learning better data representation using inference-driven metric learning. In Proceedings of the ACL 2010 Conference Short Papers, pages 377-381, Uppsala.

Digital Library

[28]

Erk, Katrin and Sebastian Padó. 2006. Shalmaneser--a toolchain for shallow semantic parsing. In Proceedings of the Fifth International Conference on Language Resources and Evaluation, pages 527-532, Genoa.

[29]

Fellbaum, Christiane, editor. 1998. WordNet: an electronic lexical database. MIT Press, Cambridge, MA.

[30]

Fillmore, Charles J. 1982. Frame semantics. In Linguistics in the Morning Calm. Hanshin Publishing Co., Seoul, pages 111-137.

[31]

Fillmore, Charles J., Christopher R. Johnson, and Miriam R. L. Petruck. 2003. Background to FrameNet. International Journal of Lexicography, 16.3:235-250.

[32]

Fleischman, Michael, Namhee Kwon, and Eduard Hovy. 2003. Maximum entropy models for FrameNet classification. In Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, pages 49-56, Sapporo.

Digital Library

[33]

Fung, Pascale and Benfeng Chen. 2004. BiFrameNet: Bilingual frame semantics resource construction by cross-lingual induction. In Proceedings of the 20th International Conference on Computational Linguistics, pages 931-937, Geneva.

Digital Library

[34]

Fürstenau, Hagen and Mirella Lapata. 2009a. Graph alignment for semi-supervised semantic role labeling. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, pages 11-20, Singapore.

Digital Library

[35]

Fürstenau, Hagen and Mirella Lapata. 2009b. Semi-supervised semantic role labeling. In Proceedings of the 12th Conference of the European Chapter of the ACL, pages 220-228, Athens.

Digital Library

[36]

Fürstenau, Hagen and Mirella Lapata. 2012. Semi-supervised semantic role labeling via structural alignment. Computational Linguistics, 38(1):135-171.

Digital Library

[37]

Gerber, Matthew and Joyce Chai. 2010. Beyond NomBank: A study of implicit arguments for nominal predicates. In Proceedings of ACL, pages 1,583-1,592, Uppsala.

Digital Library

[38]

Gildea, Daniel and Daniel Jurafsky. 2002. Automatic labeling of semantic roles. Computational Linguistics, 28(3):245-288.

Digital Library

[39]

Girju, Roxana, Preslav Nakov, Vivi Nastase, Stan Szpakowicz, Peter Turney, and Deniz Yuret. 2007. SemEval-2007 task 04: Classification of semantic relations between nominals. In Proceedings of the Fourth International Workshop on Semantic Evaluations, pages 13-18, Prague.

Digital Library

[40]

Giuglea, Ana-Maria and Alessandro Moschitti. 2006. Shallow semantic parsing based on FrameNet, VerbNet and PropBank. In Proceedings of the 17th European Conference on Artificial Intelligence, pages 563-567, Amsterdam.

Digital Library

[41]

Gropp, W., E. Lusk, and A. Skjellum. 1994. Using MPI: Portable Parallel Programming with the Message-Passing Interface. MIT Press, Cambridge, MA.

Digital Library

[42]

Haji¿, Jan, Massimiliano Ciaramita, Richard Johansson, Daisuke Kawahara, Maria Antònia Martí, Lluís Màrquez, Adam Meyers, Joakim Nivre, Sebastian Padó, Jan ¿tepánek, Pavel Stra¿ák, Mihai Surdeanu, Nianwen Xue, and Yi Zhang. 2009. The CoNLL-2009 shared task: Syntactic and semantic dependencies in multiple languages. In Proceedings of the Thirteenth Conference on Computational Natural Language Learning, pages 1-18, Boulder, CO.

Digital Library

[43]

Ide, Nancy and Jean Véronis. 1998. Introduction to the special issue on word sense disambiguation: The state of the art. Computational Linguistics, 24(1):2-40.

Digital Library

[44]

Johansson, Richard and Pierre Nugues. 2007. LTH: Semantic structure extraction using nonprojective dependency trees. In Proceedings of the 4th International Workshop on Semantic Evaluations, pages 227-230, Prague.

Digital Library

[45]

Johansson, Richard and Pierre Nugues. 2008. Dependency-based semantic role labeling of PropBank. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pages 69-78, Honolulu, HI.

Digital Library

[46]

Kingsbury, Paul and Martha Palmer. 2002. From TreeBank to PropBank. In Proceedings of the 3rd International Conference on Language Resources and Evaluation, pages 1,989-1,993, Las Palmas.

[47]

Komodakis, Nikos, Nikos Paragios, and Georgios Tziritas. 2007. MRF optimization via dual decomposition: Message-passing revisited. In Eleventh International Conference on Computer Vision, pages 1-8, Rio de Janeiro.

[48]

Koo, Terry, Alexander M. Rush, Michael Collins, Tommi Jaakkola, and David Sontag. 2010. Dual decomposition for parsing with non-projective head automata. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 1,288-1,298, Cambridge, MA.

Digital Library

[49]

Kowalski, Matthieu and Bruno Torrésani. 2009. Sparsity and persistence: Mixed norms provide simple signal models with dependent coefficients. Signal, Image and Video Processing, 3:251-264.

[50]

Lang, Joel and Mirella Lapata. 2010. Unsupervised induction of semantic roles. In Proceedings of the Human Language Technologies Conference of the North American Chapter of the Association for Computational Linguistics, pages 939-947, Los Angeles, CA.

Digital Library

[51]

Lang, Joel and Mirella Lapata. 2011. Unsupervised semantic role induction with graph partitioning. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pages 1320-1331, Edinburgh.

Digital Library

[52]

Lin, Dekang. 1993. Principle-based parsing without overgeneration. In Proceedings of the 31st Annual Meeting of the Association for Computational Linguistics, pages 112-120, Columbus, OH.

Digital Library

[53]

Lin, Dekang. 1994. Principar-an efficient, broad-coverage, principle-based parser. In Proceedings of the 15th Conference on Computational Linguistics, pages 482-488, Kyoto.

Digital Library

[54]

Lin, Dekang. 1998. Automatic retrieval and clustering of similar words. In Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, pages 768-774, Montreal.

Digital Library

[55]

Lin, Jianhua. 1991. Divergence measures based on the Shannon entropy. IEEE Transactions on Information Theory, 37(1):145-151.

Digital Library

[56]

Litkowski, Kenneth C. and Orin Hargraves. 2007. SemEval-2007 task 06:Word-sense disambiguation of prepositions. In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), pages 24-29, Prague.

Digital Library

[57]

Liu, Dong C. and Jorge Nocedal. 1989. On the limited memory BFGS method for large scale optimization. Mathematical Programming, 45(3):503-528.

[58]

Marcus, Mitchell P., Mary Ann Marcinkiewicz, and Beatrice Santorini. 1993. Building a large annotated corpus of English: the Penn treebank. Computational Linguistics, 19(2):313-330, June.

Digital Library

[59]

Màrquez, Lluís, Xavier Carreras, Kenneth C. Litkowski, and Suzanne Stevenson. 2008. Semantic role labeling: an introduction to the special issue. Computational Linguistics, 34(2):145-159, June.

Digital Library

[60]

Martins, André F. T., Mario A. T. Figueiredo, Pedro M. Q. Aguiar, Noah A. Smith, and Eric P. Xing. 2011a. An augmented Lagrangian approach to constrained MAP inference. In Proceedings of the 28th International Conference on Machine Learning, pages 169-176, Bellevue, WA.

[61]

Martins, André F. T., Noah A. Smith, Pedro M. Q. Aguiar, and Mario A. T. Figueiredo. 2011b. Dual decomposition with many overlapping components. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, pages 238-249, Edinburgh.

Digital Library

[62]

Martins, André F. T., Noah A. Smith, and Eric P. Xing. 2009. Concise integer linear programming formulations for dependency parsing. In Proceedings of the Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the AFNLP, pages 342-350, Suntec.

Digital Library

[63]

Martins, André F. T., Noah A. Smith, Eric P. Xing, Mario A. T. Figueiredo, and Pedro M. Q. Aguiar. 2010. Turbo parsers: Dependency parsing by approximate variational inference. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 34-44, Cambridge, MA.

Digital Library

[64]

Matsubayashi, Yuichiroh, Naoaki Okazaki, and Jun'ichi Tsujii. 2009. A comparative study on generalization of semantic roles in FrameNet. In Proceedings of the Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the AFNLP, pages 19-27, Suntec.

Digital Library

[65]

McDonald, Ryan, Koby Crammer, and Fernando Pereira. 2005. Online large-margin training of dependency parsers. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics, pages 91-98, Ann Arbor, MI.

Digital Library

[66]

Meyers, Adam, Ruth Reeves, Catherine Macleod, Rachel Szekely, Veronika Zielinska, Brian Young, and Ralph Grishman. 2004. The NomBank project: An interim report. In Proceedings of the NAACL-HLT Workshop on Frontiers in Corpus Annotation, pages 24-31, Boston, MA.

[67]

Moschitti, Alessandro, Paul Morarescu, and Sanda M. Harabagiu. 2003. Open-domain information extraction via automatic semantic labeling. In Ingrid Russell and Susan M. Haller, editors, Proceedings of the Sixteenth International Florida Artificial Intelligence Research Society Conference, pages 397-401, St. Augustine, FL.

[68]

Narayanan, Srini and Sanda Harabagiu. 2004. Question answering based on semantic structures. In Proceedings of the 20th International Conference on Computational Linguistics, Geneva.

Digital Library

[69]

Padó, Sebastian and Katrin Erk. 2005. To cause or not to cause: cross-lingual semantic matching for paraphrase modelling. In Proceedings of the Cross-Language Knowledge Induction Workshop, Cluj-Napoca.

[70]

Pado, Sebastian and Mirella Lapata. 2005. Cross-linguistic projection of role-semantic information. In Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, pages 859-866, Vancouver.

Digital Library

[71]

Pennacchiotti, Marco, Diego De Cao, Roberto Basili, Danilo Croce, and Michael Roth. 2008. Automatic induction of FrameNet lexical units. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pages 457-465, Honolulu, HI.

Digital Library

[72]

Pradhan, Sameer S., Wayne H. Ward, Kadri Hacioglu, James H. Martin, and Dan Jurafsky. 2004. Shallow semantic parsing using support vector machines. In Proceedings of the Human Language Technologies Conference of the North American Chapter of the Association for Computational Linguistics, pages 233-240, Boston, MA.

[73]

Punyakanok, Vasin, Dan Roth, and Wentau Yih. 2008. The importance of syntactic parsing and inference in semantic role labeling. Computational Linguistics, 34(2):257-287.

Digital Library

[74]

Punyakanok, Vasin, Dan Roth, Wen-tau Yih, and Dav Zimak. 2004. Semantic role labeling via integer linear programming inference. In Proceedings of the 20th International Conference on Computational Linguistics, pages 1,346-1,352, Geneva.

Digital Library

[75]

Ratnaparkhi, Adwait. 1996. A maximum entropy model for part-of-speech tagging. In Proceedings of the 1996 Empirical Methods in Natural Language Processing, pages 133-142, Copenhagen.

[76]

Riedel, Sebastian and James Clarke. 2006. Incremental integer linear programming for non-projective dependency parsing. In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, pages 129-137, Sydney.

Digital Library

[77]

Roth, Dan and Wen-tau Yih. 2004. A linear programming formulation for global inference in natural language tasks. In Proceedings of the Eighth Conference on Computational Natural Language Learning, pages 1-8, Boston, MA.

[78]

Ruppenhofer, Josef, Michael Ellsworth, Miriam R. L. Petruck, Christopher R. Johnson, and Jan Scheffczyk. 2006. FrameNet II: extended theory and practice. International Computer Science Institute, Berkeley, CA.

[79]

Rush, Alexander M. and Michael Collins. 2011. Exact decoding of syntactic translation models through Lagrangian relaxation. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 72-82, Portland, OR.

Digital Library

[80]

Rush, Alexander M, David Sontag, Michael Collins, and Tommi Jaakkola. 2010. On dual decomposition and linear programming relaxations for natural language processing. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 1-11, Cambridge, MA.

Digital Library

[81]

Schuler, Karin K. 2005. VerbNet: a broad-coverage, comprehensive verb lexicon. Ph.D. thesis, University of Pennsylvania.

Digital Library

[82]

Sha, Fei and Fernando Pereira. 2003. Shallow parsing with conditional random fields. In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, pages 134-141, Edmonton.

Digital Library

[83]

Shen, Dan and Mirella Lapata. 2007. Using semantic roles to improve question answering. In Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pages 12-21, Prague.

[84]

Shi, Lei and Rada Mihalcea. 2004. An algorithm for open text semantic parsing. In Proceedings of Workshop on Robust Methods in Analysis of Natural Language Data, pages 59-67, Geneva.

Digital Library

[85]

Shi, Lei and Rada Mihalcea. 2005. Putting pieces together: Combining FrameNet, VerbNet and WordNet for robust semantic parsing. In Proceedings of the 6th International Conference on Computational Linguistics and Intelligent Text Processing, pages 100-111, Mexico City.

Digital Library

[86]

Smith, David A. and Jason Eisner. 2008. Dependency parsing by belief propagation. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pages 145-156, Honolulu, HI.

Digital Library

[87]

Subramanya, Amarnag and Jeff Bilmes. 2008. Soft-supervised learning for text classification. In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing, pages 1,090-1,099, Honolulu, HI.

Digital Library

[88]

Subramanya, Amarnag, Slav Petrov, and Fernando Pereira. 2010. Efficient graph-based semi-supervised learning of structured tagging models. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing, pages 167-176, Cambridge, MA.

Digital Library

[89]

Surdeanu, Mihai, Sanda Harabagiu, John Williams, and Paul Aarseth. 2003. Using predicate-argument structures for information extraction. In Proceedings of the 41st Annual Meeting on Association for Computational Linguistics, pages 8-15, Sapporo.

Digital Library

[90]

Surdeanu, Mihai, Richard Johansson, Adam Meyers, Lluís Màrquez, and Joakim Nivre. 2008. The CoNLL 2008 shared task on joint parsing of syntactic and semantic dependencies. In Proceedings of the Twelfth Conference on Computational Natural Language Learning, pages 159-177, Manchester.

Digital Library

[91]

Szummer, Martin and Tommi Jaakkola. 2001. Partially labeled classification with Markov random walks. In Advances in Neural Information Processing Systems 14, pages 945-952, Vancouver.

[92]

Talukdar, Partha Pratim and Koby Crammer. 2009. New regularized algorithms for transductive learning. In Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, pages 442-457, Bled.

Digital Library

[93]

Thompson, Cynthia A., Roger Levy, and Christopher D. Manning. 2003. A generative model for semantic role labeling. In Proceedings of the European Conference on Machine Learning, pages 397-408, Cavtat-Dubrovnik.

[94]

Titov, Ivan and Alexandre Klementiev. 2012. A Bayesian approach to unsupervised semantic role induction. In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics, pages 12-22, Avignon.

Digital Library

[95]

Toutanova, Kristina, Aria Haghighi, and Christopher Manning. 2005. Joint learning improves semantic role labeling. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics, pages 589-596, Ann Arbor, MI.

Digital Library

[96]

Turian, Joseph, Lev-Arie Ratinov, and Yoshua Bengio. 2010. Word representations: A simple and general method for semi-supervised learning. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pages 384-394, Uppsala.

Digital Library

[97]

Weston, Jason, Frédéric Ratle, and Ronan Collobert. 2008. Deep learning via semi-supervised embedding. In Proceedings of the 25th International Conference on Machine Learning, pages 1,168-1,175, Helsinki.

Digital Library

[98]

Xue, Nianwen and Martha Palmer. 2004. Calibrating features for semantic role labeling. In Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing, pages 88-94, Barcelona.

[99]

Yi, Szu-ting, Edward Loper, and Martha Palmer. 2007. Can semantic roles generalize across genres? In Proceedings of the Human Language Technologies Conference of the North American Chapter of the Association for Computational Linguistics, pages 548-555, Rochester, NY.

[100]

Zhu, Xiaojin. 2008. Semi-supervised learning literature survey. Available at http://pages.cs.wisc.edu/~jerryzhu/pub/ssl_survey.pdf. Last Accessed July 2013.

[101]

Zhu, Xiaojin, Zoubin Ghahramani, and John Lafferty. 2003. Semi-supervised learning using Gaussian fields and harmonic functions. In Proceedings of the 20th International Conference on Machine Learning, pages 912-919, Washington, DC.

Digital Library

Cited By

Anwar SShelmanov AArefyev NPanchenko ABiemann C(2024)Text augmentation for semantic frame induction and parsingLanguage Resources and Evaluation10.1007/s10579-023-09679-858:2(363-408)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10579-023-09679-8
Su XLi RLi XChang BHu ZHan XYan Z(2023)A Span-based Target-aware Relation Model for Frame-semantic ParsingACM Transactions on Asian and Low-Resource Language Information Processing10.1145/356958122:3(1-24)Online publication date: 10-Mar-2023
https://dl.acm.org/doi/10.1145/3569581
Hromei CCristofori LCroce DBasili R(2022)Embedding Contextual Information in Seq2seq Models for Grounded Semantic Role LabelingAIxIA 2022 – Advances in Artificial Intelligence10.1007/978-3-031-27181-6_33(472-485)Online publication date: 28-Nov-2022
https://dl.acm.org/doi/10.1007/978-3-031-27181-6_33
Show More Cited By

Frame-semantic parsing
1. Applied computing
  1. Arts and humanities
2. Computing methodologies
  1. Artificial intelligence

Recommendations

Probabilistic frame-semantic parsing
HLT '10: Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics

This paper contributes a formalization of frame-semantic parsing as a structure prediction problem and describes an implemented parser that transforms an English sentence into a frame-semantic representation. It finds words that evoke FrameNet frames, ...
Frame-semantic web: a case study for Korean
ISWC-PD'14: Proceedings of the 2014 International Conference on Posters & Demonstrations Track - Volume 1272

FrameNet itself can become a resource for the Semantic Web. It can be represented in RDF. However, mapping FrameNet to other resources such as Wikipedia for building a knowledge base becomes more common practice. By such mapping, FrameNet can be ...
Semi-supervised frame-semantic parsing for unknown predicates
HLT '11: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1

We describe a new approach to disambiguating semantic frames evoked by lexical predicates previously unseen in a lexicon or annotated data. Our approach makes use of large amounts of unlabeled data in a graph-based semi-supervised learning framework. We ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Computational Linguistics

Computational Linguistics Volume 40, Issue 1

March 2014

248 pages

ISSN:0891-2017

EISSN:1530-9312

Issue’s Table of Contents

Publisher

MIT Press

Cambridge, MA, United States

Publication History

Published: 01 March 2014

Published in COLI Volume 40, Issue 1

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

33
Total Citations
View Citations
210
Total Downloads

Downloads (Last 12 months)7
Downloads (Last 6 weeks)1

Reflects downloads up to 13 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Anwar SShelmanov AArefyev NPanchenko ABiemann C(2024)Text augmentation for semantic frame induction and parsingLanguage Resources and Evaluation10.1007/s10579-023-09679-858:2(363-408)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10579-023-09679-8
Su XLi RLi XChang BHu ZHan XYan Z(2023)A Span-based Target-aware Relation Model for Frame-semantic ParsingACM Transactions on Asian and Low-Resource Language Information Processing10.1145/356958122:3(1-24)Online publication date: 10-Mar-2023
https://dl.acm.org/doi/10.1145/3569581
Hromei CCristofori LCroce DBasili R(2022)Embedding Contextual Information in Seq2seq Models for Grounded Semantic Role LabelingAIxIA 2022 – Advances in Artificial Intelligence10.1007/978-3-031-27181-6_33(472-485)Online publication date: 28-Nov-2022
https://dl.acm.org/doi/10.1007/978-3-031-27181-6_33
Guo SGuan YLi RLi XTan H(2021)Frame-based Multi-level Semantics Representation for text matching▪Knowledge-Based Systems10.1016/j.knosys.2021.107454232:COnline publication date: 28-Nov-2021
https://dl.acm.org/doi/10.1016/j.knosys.2021.107454
Žabokrtský ZZeman DŠevčíková M(2020)Sentence Meaning Representations Across LanguagesComputational Linguistics10.1162/coli_a_0038546:3(605-665)Online publication date: 1-Nov-2020
https://dl.acm.org/doi/10.1162/coli_a_00385
Mandal SGandhi RSiy H(2020)Modular norm models: practical representation and analysis of contractual rights and obligationsRequirements Engineering10.1007/s00766-019-00323-y25:3(383-412)Online publication date: 1-Sep-2020
https://dl.acm.org/doi/10.1007/s00766-019-00323-y
Ustalov DPanchenko ABiemann CPonzetto S(2019)WatsetComputational Linguistics10.1162/coli_a_0035445:3(423-479)Online publication date: 1-Sep-2019
https://dl.acm.org/doi/10.1162/coli_a_00354
Marques ADumas MPfahl DApel SRusso A(2019)Helping developers search and locate task-relevant information in natural language documentsProceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3338906.3341459(1168-1171)Online publication date: 12-Aug-2019
https://dl.acm.org/doi/10.1145/3338906.3341459
Lee ELynn HKim HYeom SKim PHung CPapadopoulos G(2019)Semantic analysis for paraphrase identification using semantic role labelingProceedings of the 34th ACM/SIGAPP Symposium on Applied Computing10.1145/3297280.3300200(2135-2138)Online publication date: 8-Apr-2019
https://dl.acm.org/doi/10.1145/3297280.3300200
Barzdins GGosko DBarzdins PLavrinovics UBernans GCelms E(2019)RDF* Graph Database as Interlingua for the TextWorld Challenge2019 IEEE Conference on Games (CoG)10.1109/CIG.2019.8848012(1-2)Online publication date: 20-Aug-2019
https://dl.acm.org/doi/10.1109/CIG.2019.8848012
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Issue’s Table of Contents