Decomp-aligned annotations of word senses, semantic roles, and event properties on the Universal Dependencies treebank
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README.md

README.md

Universal Decompositional Semantics on Universal Dependencies

Authors: Aaron Steven White, Drew Reisinger, Keisuke Sakaguchi, Tim Vieira, Sheng Zhang, Rachel Rudinger, Kyle Rawlins, and Benjamin Van Durme

Contact: {aswhite,dreisin2,kgr}@jhu.edu, {keisuke, vandurme, rudinger}@cs.jhu.edu, {zhangsheng.zero, tim.f.vieira}@gmail.com

Release date: Nov 1, 2016

Overview

This release consists of three datasets along with materials that were used to collect those data:

  • Semantic Proto-Roles (v2.x): ordinal likelihood judgments for relational properties entailed of arguments by their predicate
  • It Happened (v1.0): binary judgments of whether an eventuality described by a predicated happened along with an ordinal confidence judgment
  • WordNet WSD (v1.0): binary judgments of whether a particular nominal argument head has a particular WordNet sense

Each directory in data/ contains a README with further descriptions of each dataset. For a more detailed description of these datasets as well as details of the item construction and collection methods, please see the following paper:

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. In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 1713–1723, Austin, Texas, November 1-5, 2016.

If you make use of this data set in a presentation or publication, we ask that you please cite this paper.

Acknowledgments

This research was supported by the JHU HLTCOE, DARPA DEFT, DARPA LORELEI, and NSF INSPIRE BCS-1344269. The U.S. Government is authorized to reproduce and distribute reprints of the paper for Governmental purposes. The views and conclusions contained here are those of the authors and should not be interpreted as representing official policies or endorsements of DARPA or the U.S. Government.