Triple

T6113563
Position Surface form Disambiguated ID Type / Status
Subject Tepanec E136303 entity
Predicate majorCity P316 FINISHED
Object Tacuba E60721 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: Tacuba | Statement: [Tepanec, majorCity, Tacuba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tacuba
Context triple: [Tepanec, majorCity, Tacuba]
  • A. Tacuba chosen
    Tacuba is a historic neighborhood in Mexico City known for its colonial-era architecture and role as a former pre-Hispanic town.
  • B. Tecali
    Tecali is a Mexican town renowned for its traditional crafts, particularly the production of Talavera pottery and stonework.
  • C. Tuxpan
    Tuxpan is a town and municipality in the Mexican state of Nayarit, known for its agricultural economy and traditional cultural festivals.
  • D. Tuxpan
    Tuxpan is a port city in the Mexican state of Veracruz, known for its Gulf Coast location and historical role as a departure point in the Cuban Revolution.
  • E. San Luis Talpa
    San Luis Talpa is a municipality in the La Paz department of El Salvador, located near the country’s main international airport and known for its role as a transit and service hub for travelers.
  • 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_69c0089ea6f88190b349be53e04b4f5f completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bbf2ee4819097af2cce9248bf4e completed March 22, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c12566fb908190bb9c27fe64f618cd completed March 23, 2026, 11:35 a.m.
Created at: March 22, 2026, 4:14 p.m.