Viviane Torres da Silva

Fixing paper assignments

  1. Please select all papers that belong to the same person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here

2024

pdf bib
Deductive Verification of LLM Generated SPARQL Queries
Alexandre Rademaker | Guilherme Lima | Sandro Rama Fiorini | Viviane Torres da Silva
Proceedings of the Workshop on Deep Learning and Linked Data (DLnLD) @ LREC-COLING 2024

Considering the increasing applications of Large Language Models (LLMs) to many natural language tasks, this paper presents preliminary findings on developing a verification component for detecting hallucinations of an LLM that produces SPARQL queries from natural language questions. We suggest a logic-based deductive verification of the generated SPARQL query by checking if the original NL question’s deep semantic representation entails the SPARQL’s semantic representation.
Search
Co-authors
Venues
Fix data