Triple

T1495521
Position Surface form Disambiguated ID Type / Status
Subject Mexican Plateau E29675 entity
Predicate passesThrough P225 FINISHED
Object Hidalgo E31143 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: Hidalgo | Statement: [Mexican Plateau, passesThrough, Hidalgo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hidalgo
Context triple: [Mexican Plateau, passesThrough, Hidalgo]
  • A. Hidalgo chosen
    Hidalgo is a central Mexican state known for its mountainous terrain, rich mining history, and diverse indigenous cultural heritage.
  • B. Navojoa
    Navojoa is a city in the southern part of the state of Sonora, Mexico, known as an agricultural and commercial center in the Mayo River valley.
  • C. San Felipe
    San Felipe is a historic city in central Chile known for its agricultural surroundings and role as a commercial and administrative center in the Aconcagua Valley.
  • D. Navarro
    Navarro is a Spanish surname borne by numerous notable individuals across fields such as film, sports, politics, and academia.
  • E. Dolores Hidalgo
    Dolores Hidalgo is a historic town in the Mexican state of Guanajuato, renowned as the cradle of Mexico’s independence movement and named after priest and revolutionary leader Miguel Hidalgo y Costilla.
  • 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6ec70c48190a94f6e1002848eae completed March 1, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad2331b49881908672251bb86418df completed March 8, 2026, 7:20 a.m.
Created at: March 1, 2026, 8:12 p.m.