Decomp

The Decompositional Semantics Initiative (Decomp) is a collection of efforts aimed at collecting and modeling human annotations of meaning via the decomposition of lexical and phrasal meanings into a small set of component parts. Decomp is supported by DARPA AIDA, DARPA KAIROS, and IARPA BETTER.

Decomp is a large project and so only research products authored by core FACTS.lab members are listed below. A full list of publications, presentations, and available data can be found at decomp.io.

Papers

Stengel-Eskin, E. A.S. White, S. Zhang, & B. Van Durme. 2019. Transductive Parsing for Universal Decompositional Semantics. arXiv:1910.10138 [cs.CL].

White, A.S., E. Stengel-Eskin, S. Vashishtha, V. Govindarajan, D. Reisinger, T. Vieira, K. Sakaguchi, S. Zhang, F. Ferraro, R. Rudinger, K. Rawlins, & B. Van Durme. 2019. The Universal Decompositional Semantics Dataset and Decomp Toolkit. Accepted to Proceedings of the Twelfth International Conference on Language Resources and Evaluation (LREC 2020).

Vashishtha, S., B. Van Durme, & A.S. White. 2019. Fine-Grained Temporal Relation Extraction. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019), Florence, Italy, July 29-31, 2019.

Govindarajan, V.S., B. Van Durme, & A.S. White. 2019. Decomposing Generalization: Models of Generic, Habitual, and Episodic Statements. Transactions of the Association for Computational Linguistics 7: 501–517.

White, A.S., R. Rudinger, K. Rawlins, & B. Van Durme. 2018. Lexicosyntactic Inference in Neural Models. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31-November 4, 2018.

Poliak, A., A. Haldar, R. Rudinger, J.E. Hu, E. Pavlick, A.S. White, & B. Van Durme. 2018. Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation. Proceedings of 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31-November 4, 2018.

Rudinger, R., A. S. White, & B. Van Durme. 2018. Neural Models of Factuality. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics, New Orleans, LA, June 1 – June 6, 2018.

White, A. S., P. Rastogi, K. Duh, & B. Van Durme. 2017. Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework. Proceedings of the The 8th International Joint Conference on Natural Language Processing, pages 996–1005, Taipei, Taiwan, November 27 – December 1, 2017.

White, A. S., K. Rawlins, & B. Van Durme. 2017. The Semantic Proto-Role Linking Model. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pages 92–98, Valencia, Spain, April 3-7, 2017.

White, A. S., D. Reisinger, K. Sakaguchi, T. Vieira, S. Zhang, R. Rudinger, K. Rawlins, & B. Van Durme. 2016. Universal decompositional semantics on universal dependencies. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 1713–1723, Austin, Texas, November 1-5, 2016.

MegaAttitude

The MegaAttitude Project aims to collect large-scale annotation sets of the selectional behavior of clause-embedding verbs, adjectives, and nouns, based on human acceptability, veridicality, and similarity judgments. It is supported by a National Science Foundation collaborative grant (BCS-1748969/BCS-1749025).

Papers

White, A.S. & K. Rawlins. 2020. Frequency, acceptability, and selection: A case study of clause-embedding. Accepted to Glossa.

An, H.Y. & A.S. White. 2020. The lexical and grammatical sources of neg-raising inferences. Proceedings of the Society for Computation in Linguistics 3:23, pages 220-233. New Orleans, Louisiana, January 2-5, 2020.

White, A.S. 2019. Lexically triggered veridicality inferences. In Handbook of Pragmatics, eds. J. Östman & J. Verschueren. John Benjamins Publishing Company.

White, A.S. 2019. Nothing’s wrong with believing (or hoping) whether. Under revision for Semantics and Pragmatics.

White, A. S., R. Rudinger, K. Rawlins, & B. Van Durme. 2018. Lexicosyntactic Inference in Neural Models. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31-November 4, 2018.

White, A. S. & K. Rawlins. 2018. The role of veridicality and factivity in clause selection. To appear in the Proceedings of the 48th Meeting of the North East Linguistic Society.

White, A. S. & K. Rawlins. 2016. A computational model of S-selection. In Semantics and Linguistic Theory 26, 641-663. Ithaca, NY: CLC Publications.