mlsanityData to 7 Oct 2026

Decomposing and Recomposing Event Structure

arXiv 2103.10387 ↗First posted 18 Mar 2021cs.CLcited by 5

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Abstract (arXiv)

We present an event structure classification empirically derived from inferential properties annotated on sentence- and document-level Universal Decompositional Semantics (UDS) graphs. We induce this classification jointly with semantic role, entity, and event-event relation classifications using a document-level generative model structured by these graphs. To support this induction, we augment existing annotations found in the UDS1.0 dataset, which covers the entirety of the English Web Treebank, with an array of inferential properties capturing fine-grained aspects of the temporal and aspectual structure of events. The resulting dataset (available at decomp.io) is the largest annotation of event structure and (partial) event coreference to date.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 10 of its 70 references that are in the map. First posted on arXiv 18 Mar 2021.

Builds on

10 of 70 references.

References · 10

  1. 2019"Going on a vacation" takes longer than "Going for a walk": A Study of Temporal Commonsense Understandingcited by 121
  2. 2020Joint Constrained Learning for Event-Event Relation Extractioncited by 53
  3. 2020Temporal Common Sense Acquisition with Minimal Supervisioncited by 38
  4. 2019Fine-Grained Temporal Relation Extractioncited by 20
  5. 2019Decomposing Generalization: Models of Generic, Habitual, and Episodic Statementscited by 10
  6. 2019The Universal Decompositional Semantics Dataset and Decomp Toolkitcited by 10
  7. 2018Neural-Davidsonian Semantic Proto-role Labelingcited by 9
  8. 2020Natural Language Inference with Mixed Effectscited by 9
  9. 2019Universal Decompositional Semantic Parsingcited by 8
  10. 2020A Broad-Coverage Deep Semantic Lexicon for Verbscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 0; 2025: 0; 2026: 1.

5 papers.