Abstract
The paper investigates the extent of the support semi-automatic analysis can provide for the specific task of assigning Hohfeldian relations of Duty, using the General Architecture for Text Engineering tool for the automated extraction of Duty instances and the bearers of associated roles. The outcome of the analysis supports scholars in identifying Hohfeldian structures in legal text when performing close reading of the texts. A cyclic workflow involving automated annotation and expert feedback will incrementally increase the quality and coverage of the automatic extraction process, and increasingly reduce the amount of manual work required of the scholar.- Anthology ID:
- L16-1059
- Volume:
- Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
- Month:
- May
- Year:
- 2016
- Address:
- Portorož, Slovenia
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 379–384
- Language:
- URL:
- https://aclanthology.org/L16-1059
- DOI:
- Cite (ACL):
- Wim Peters and Adam Wyner. 2016. Legal Text Interpretation: Identifying Hohfeldian Relations from Text. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 379–384, Portorož, Slovenia. European Language Resources Association (ELRA).
- Cite (Informal):
- Legal Text Interpretation: Identifying Hohfeldian Relations from Text (Peters & Wyner, LREC 2016)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/L16-1059.pdf