Triple

T10747342
Position Surface form Disambiguated ID Type / Status
Subject State of Nayarit E253484 entity
Predicate capital P234 FINISHED
Object Tepic E173358 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: Tepic | Statement: [State of Nayarit, capital, Tepic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tepic
Context triple: [State of Nayarit, capital, Tepic]
  • A. Tepic chosen
    Tepic is the capital city of the Mexican state of Nayarit, known as a regional commercial and transportation hub in western Mexico.
  • B. Tepatitlán de Morelos
    Tepatitlán de Morelos is a prominent city in Mexico known for its agricultural production, religious traditions, and vibrant regional culture.
  • C. Tulancingo
    Tulancingo is a historic city in central Mexico known for its colonial architecture, regional commerce, and cultural traditions within the state of Hidalgo.
  • D. 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).
  • E. Juanacatlán
    Juanacatlán is a Mexico City Metro station on Line 1, located near the Condesa and San Miguel Chapultepec neighborhoods.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d711b9242c81908dbf3fa155159b3c completed April 9, 2026, 2:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69deb0a03a1481908edb933b1613a027 completed April 14, 2026, 9:24 p.m.
Created at: April 8, 2026, 9:15 p.m.