Triple

T6830767
Position Surface form Disambiguated ID Type / Status
Subject Cosalá E157130 entity
Predicate hasMunicipalSeat P1474 FINISHED
Object Cosalá E157130 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: Cosalá | Statement: [Cosalá, hasMunicipalSeat, Cosalá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cosalá
Context triple: [Cosalá, hasMunicipalSeat, Cosalá]
  • A. Cosalá chosen
    Cosalá is a historic mining town and municipality in the Mexican state of Sinaloa, known for its well-preserved colonial architecture and designation as a Pueblo Mágico (Magical Town).
  • B. Comayagüela
    Comayagüela is a major urban district of Honduras that, together with Tegucigalpa, forms the country’s capital area.
  • C. Alcohuaz
    Alcohuaz is a small rural village in Chile’s Elqui Valley, known for its high-altitude vineyards, pisco production, and clear skies for stargazing.
  • D. Sibaté
    Sibaté is a municipality in central Colombia known for its agricultural production and proximity to Bogotá within the Cundinamarca Department.
  • E. Choloma
    Choloma is a rapidly growing industrial city in northern Honduras known for its large concentration of maquiladora factories and manufacturing activity.
  • 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_69c6882a5b5c8190917a7db9ed36bad1 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d62820808190ad3c244893e88699 completed March 27, 2026, 7:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723f73eec81908c666888a19c0b29 completed March 28, 2026, 12:42 a.m.
Created at: March 27, 2026, 2:18 p.m.