Triple

T13303246
Position Surface form Disambiguated ID Type / Status
Subject University of Girona E316866 entity
Predicate shortName P43 FINISHED
Object UdG E316866 NE FINISHED

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: UdG | Statement: [University of Girona, shortName, UdG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UdG
Context triple: [University of Girona, shortName, UdG]
  • A. University of Girona chosen
    The University of Girona is a public higher education and research institution located in the city of Girona, Catalonia, Spain.
  • B. Open University of Catalonia
    The Open University of Catalonia is an online-focused Catalan university known for its distance education programs and digital learning model.
  • C. Universitat Autònoma de Barcelona
    The Universitat Autònoma de Barcelona is a major public research university in Catalonia, Spain, known for its strong academic programs and extensive campus near Barcelona.
  • D. University of Lleida
    The University of Lleida is a public higher education and research institution located in the city of Lleida, Catalonia, Spain.
  • E. Universitat de Manresa
    Universitat de Manresa is a higher education institution located in the Catalan city of Manresa, offering university-level studies and professional training.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a60eb08190bf0dc098ca7dc342 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716e161008190a48275ef54225d56 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:28 p.m.