NarrativeTime: Dense Temporal Annotation on a Timeline
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Abstract (arXiv)
For the past decade, temporal annotation has been sparse: only a small portion of event pairs in a text was annotated. We present NarrativeTime, the first timeline-based annotation framework that achieves full coverage of all possible TLinks. To compare with the previous SOTA in dense temporal annotation, we perform full re-annotation of TimeBankDense corpus, which shows comparable agreement with a significant increase in density. We contribute TimeBankNT corpus (with each text fully annotated by two expert annotators), extensive annotation guidelines, open-source tools for annotation and conversion to TimeML format, baseline results, as well as quantitative and qualitative analysis of inter-annotator agreement.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Aug 2019.
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Citing papers per year: 2024: 1; 2025: 3.
4 papers.
- 2025Beyond Pairwise: Global Zero-shot Temporal Graph Generationcited by 2
- 2024EventFull: Complete and Consistent Event Relation Annotationcited by 1
- 2025Transformer-Based Temporal Information Extraction and Application: A Reviewcited by 1
- 2025Early Risk Prediction with Temporally and Contextually Grounded Clinical Language Processingcited by 0
- 2025Early Risk Prediction with Temporally and Contextually Grounded Clinical Language Processing27 Nov 2025
- 2025Transformer-Based Temporal Information Extraction and Application: A Review10 Apr 2025
- 2025Beyond Pairwise: Global Zero-shot Temporal Graph Generation16 Feb 2025
- 2024EventFull: Complete and Consistent Event Relation Annotation17 Dec 2024