Triple

T20167757
Position Surface form Disambiguated ID Type / Status
Subject National University of Piura E491870 entity
Predicate locatedIn P40 FINISHED
Object Piura 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: Piura | Statement: [National University of Piura, locatedIn, Piura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Piura
Context triple: [National University of Piura, locatedIn, Piura]
  • A. Piura chosen
    Piura is a major city in northwestern Peru known for its colonial architecture, warm climate, and role as a commercial and agricultural hub near the Pacific coast.
  • B. Piura Region
    Piura Region is a coastal region in northwestern Peru known for its warm climate, beaches, and agricultural production.
  • C. Tumbes
    Tumbes is a coastal city in northwestern Peru near the border with Ecuador, known for its mangrove forests and tropical climate.
  • D. Chimbote
    Chimbote is a coastal city in north-central Peru known for its fishing industry and port on the Pacific Ocean.
  • E. Talara
    Talara is a coastal city in northwestern Peru known for its important oil industry and nearby Pacific beaches.
  • 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66845cb588190820c50eea0c40d83 completed April 20, 2026, 5:54 p.m.
Created at: April 11, 2026, 11:35 p.m.