Zero-shot Event Extraction

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

No dataset record in the archive lists this task.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

4 shown of 4 papers with code (11 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• LEMONADE: A Large Multilingual Expert-Annotated Abstractive Event Dataset for the Real World
  1 Jun 2025 1 repository listed
  This paper presents LEMONADE, a large-scale conflict event dataset comprising 39, 786 events across 20 languages and 171 countries, with extensive coverage of region-specific entities.
• GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction
  5 Oct 2023 1 repository listed Syntology ran 18 of 25 samples · 7 unverified
  In this paper, we propose GoLLIE (Guideline-following Large Language Model for IE), a model able to improve zero-shot results on unseen IE tasks by virtue of being fine-tuned to comply with annotation guidelines.
• Efficient Zero-shot Event Extraction with Context-Definition Alignment
  9 Nov 2022 1 repository listed
  We argue that using the static embedding of the event type name might not be enough because a single word could be ambiguous, and we need a sentence to define the type semantics accurately.
• Document-Level Event Argument Extraction by Conditional Generation
  13 Apr 2021 1 repository listed Syntology ran 0 of 11 samples · 11 unverified
  On the task of argument extraction, we achieve an absolute gain of 7.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.