Triple

T12338119
Position Surface form Disambiguated ID Type / Status
Subject Tixtla E294144 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: [Tixtla, locatedIn, Guerrero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guerrero
Context triple: [Tixtla, 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 Aztec
    Guerrero Aztec is an indigenous Nahuatl-speaking community from the Mexican state of Guerrero, known for preserving traditional Aztec cultural and linguistic heritage.
  • E. 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.
  • 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f678698819091462b44ff3435f6 completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62aa7e33c819084e5673a5fb8cac7 completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:53 p.m.