Evidence Types, Credibility Factors, and Patterns or Soft Rules for Weighing Conflicting Evidence: Argument Mining in the Context of Legal Rules Governing Evidence Assessment

Vern R. Walker, Dina Foerster, Julia Monica Ponce, Matthew Rosen


Abstract
This paper reports on the results of an empirical study of adjudicatory decisions about veterans’ claims for disability benefits in the United States. It develops a typology of kinds of relevant evidence (argument premises) employed in cases, and it identifies factors that the tribunal considers when assessing the credibility or trustworthiness of individual items of evidence. It also reports on patterns or “soft rules” that the tribunal uses to comparatively weigh the probative value of conflicting evidence. These evidence types, credibility factors, and comparison patterns are developed to be inter-operable with legal rules governing the evidence assessment process in the U.S. This approach should be transferable to other legal and non-legal domains.
Anthology ID:
W18-5209
Volume:
Proceedings of the 5th Workshop on Argument Mining
Month:
November
Year:
2018
Address:
Brussels, Belgium
Editors:
Noam Slonim, Ranit Aharonov
Venue:
ArgMining
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
68–78
Language:
URL:
https://aclanthology.org/W18-5209
DOI:
10.18653/v1/W18-5209
Bibkey:
Cite (ACL):
Vern R. Walker, Dina Foerster, Julia Monica Ponce, and Matthew Rosen. 2018. Evidence Types, Credibility Factors, and Patterns or Soft Rules for Weighing Conflicting Evidence: Argument Mining in the Context of Legal Rules Governing Evidence Assessment. In Proceedings of the 5th Workshop on Argument Mining, pages 68–78, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Evidence Types, Credibility Factors, and Patterns or Soft Rules for Weighing Conflicting Evidence: Argument Mining in the Context of Legal Rules Governing Evidence Assessment (Walker et al., ArgMining 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-5209.pdf