Triple

T2979103
Position Surface form Disambiguated ID Type / Status
Subject Mexican Federal Highway 45 E80467 entity
Predicate connectsCity P4245 FINISHED
Object Celaya E329258 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: Celaya | Statement: [Mexican Federal Highway 45, connectsCity, Celaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Celaya
Context triple: [Mexican Federal Highway 45, connectsCity, Celaya]
  • A. Celaya chosen
    Celaya is a major city and industrial municipality in the Mexican state of Guanajuato, known for its manufacturing sector and traditional cajeta (goat’s milk caramel).
  • B. Monclova
    Monclova is an industrial city in northern Mexico known as a major steel-producing center in the state of Coahuila.
  • C. Irapuato
    Irapuato is a Mexican professional football club based in the city of Irapuato, Guanajuato, known for its passionate fan base and history in the country’s lower divisions.
  • D. Xalapa
    Xalapa is a city in eastern Mexico known as the capital and cultural center of the state of Veracruz.
  • E. Chilpancingo
    Chilpancingo is a Mexico City Metro station on Line 9 located in the central area of the city, serving neighborhoods such as Colonia Condesa and Roma.
  • 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_69ad8b15f6ac8190be5fd16a33edcb4f completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad999cca40819082e2d6d10bdb7872 completed March 8, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdb8d89e248190a9cd92e9f61697f8 completed March 20, 2026, 9:15 p.m.
Created at: March 8, 2026, 2:58 p.m.