Triple

T10784183
Position Surface form Disambiguated ID Type / Status
Subject Amuzgo language E254409 entity
Predicate spokenInRegion P7445 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: [Amuzgo language, spokenInRegion, Guerrero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guerrero
Context triple: [Amuzgo language, spokenInRegion, 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_69d6aa609f008190a294200aefcb7bd5 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d732d2e7cc8190a4cb9a4d7c76ab15 completed April 9, 2026, 5:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69de5609bf9c81908f47591f74c04701 completed April 14, 2026, 2:58 p.m.
Created at: April 8, 2026, 9:17 p.m.