Triple

T13300390
Position Surface form Disambiguated ID Type / Status
Subject Jalapa E316794 entity
Predicate alternateName P39 FINISHED
Object Xalapa E80059 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: Xalapa | Statement: [Jalapa, alternateName, Xalapa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xalapa
Context triple: [Jalapa, alternateName, Xalapa]
  • A. Xalapa chosen
    Xalapa is a city in eastern Mexico known as the capital and cultural center of the state of Veracruz.
  • B. Celaya
    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).
  • C. 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.
  • D. Chilpancingo
    Chilpancingo is a city in southern Mexico that serves as the capital of the state of Guerrero and played a key role in the country’s independence movement.
  • E. Zacatepec
    Zacatepec is a Mexican professional football club historically known for competing in the country's top divisions and developing notable players.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a43ed88190a8dbbbd7d6d62dc4 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8c288c08190af46fe7d114df338 completed May 3, 2026, 9:06 p.m.
Created at: April 9, 2026, 9:28 p.m.