Triple

T21534561
Position Surface form Disambiguated ID Type / Status
Subject Jorge Guillén E531317 entity
Predicate employer P7 FINISHED
Object University of Murcia NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: University of Murcia | Statement: [Jorge Guillén, employer, University of Murcia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: University of Murcia
Context triple: [Jorge Guillén, employer, University of Murcia]
  • A. University of Murcia chosen
    The University of Murcia is a public higher education and research institution located in the city of Murcia in southeastern Spain.
  • B. University of Málaga
    The University of Málaga is a public higher education and research institution located in the city of Málaga in southern Spain.
  • C. University of Alicante
    The University of Alicante is a Spanish public university located near the city of Alicante, known for its modern campus and strong programs in fields such as economics, law, engineering, and social sciences.
  • D. University of Almería
    The University of Almería is a public higher education and research institution located in the city of Almería in southeastern Spain.
  • E. University of Valencia
    The University of Valencia is one of Spain’s oldest and most prestigious public universities, renowned for its research and teaching across a wide range of disciplines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0c45e5b8881908ac18fc2f493b114 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee9d0b9888819094e424d33c14d5d0 completed April 26, 2026, 11:17 p.m.
Created at: April 16, 2026, 6:27 p.m.