Triple

T2467984
Position Surface form Disambiguated ID Type / Status
Subject University of Salamanca E55297 entity
Predicate locatedIn P40 FINISHED
Object Salamanca E55297 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: Salamanca | Statement: [University of Salamanca, locatedIn, Salamanca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salamanca
Context triple: [University of Salamanca, locatedIn, Salamanca]
  • A. Salamanca chosen
    Salamanca is a historic city in western Spain renowned for its ancient university, golden sandstone architecture, and well-preserved medieval old town.
  • B. Salamanca
    Salamanca is an industrial city in central Mexico known for its major oil refinery and role in the country's petrochemical sector.
  • C. Salamanca
    Salamanca is a Chilean town and municipality in the Coquimbo Region, known for its agricultural production and location in the Choapa Valley.
  • D. Alcalá de Henares
    Alcalá de Henares is a historic Spanish city east of Madrid, renowned as the birthplace of Miguel de Cervantes and for its well-preserved university and medieval architecture.
  • E. Burgos
    Burgos is a historic city in northern Spain known for its medieval architecture and its prominent role during the Spanish Civil War.
  • 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_69ab49e3622c8190ad22afa2c4fbb807 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd134684c8190bc62c0af22d75538 completed March 7, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69af179f90e881909c09edb961b13a75 completed March 9, 2026, 6:55 p.m.
Created at: March 6, 2026, 9:44 p.m.