Triple

T10957519
Position Surface form Disambiguated ID Type / Status
Subject Iguala E258883 entity
Predicate locatedIn P40 FINISHED
Object Guerrero E50767 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: Guerrero | Statement: [Iguala, locatedIn, Guerrero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guerrero
Context triple: [Iguala, locatedIn, Guerrero]
  • A. Guerrero chosen
    Guerrero is a coastal state in southwestern Mexico known for its mountainous terrain, including part of the Sierra Madre del Sur, and popular tourist destinations such as Acapulco.
  • B. Guerrero
    Guerrero is a Mexico City neighborhood and metro station area known for its central location and connectivity within the capital’s transit system.
  • C. Guerrero
    Guerrero is a resourceful and enigmatic former government operative turned private investigator’s associate from the television series "Human Target."
  • D. Guerrero Negro
    Guerrero Negro is a town in Baja California Sur, Mexico, best known for its large salt production facilities and as a prime destination for gray whale watching.
  • E. Guerro
    Guerro is a minor tributary stream associated with the Panaro River in northern Italy.
  • 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d771260e9881909401a7a7466e1b8a completed April 9, 2026, 9:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d7439204819092fcd061a161fd7b completed April 18, 2026, 12:58 a.m.
Created at: April 8, 2026, 9:23 p.m.