Triple

T13847699
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Soacha E332850 entity
Predicate episcopalSee P2276 FINISHED
Object Soacha E32519 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: Soacha | Statement: [Diocese of Soacha, episcopalSee, Soacha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soacha
Context triple: [Diocese of Soacha, episcopalSee, Soacha]
  • A. Soacha chosen
    Soacha is a rapidly growing industrial and residential city in central Colombia, located just southwest of Bogotá in the department of Cundinamarca.
  • B. Sogamoso
    Sogamoso is a Colombian city in the Andean region known historically as a major religious and cultural center of the Muisca civilization and today for its industry and mining.
  • C. Yopal
    Yopal is a city in eastern Colombia that serves as the main urban and economic center of the Llanos (plains) region in the Casanare Department.
  • D. Tumaco
    Tumaco is a coastal city and municipality in southwestern Colombia, known for its Afro-Colombian culture, Pacific beaches, and rich pre-Hispanic goldworking heritage.
  • E. Calarcá
    Calarcá is a Colombian town and municipality in the coffee-growing Quindío Department, known for its cultural heritage and role in the Coffee Cultural Landscape.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02b2a9788190b164760adec64ef6 completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0f189008190bb9afeef42564a33 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.