Triple

T7739477
Position Surface form Disambiguated ID Type / Status
Subject Norte de Santander Department E175467 entity
Predicate hasMunicipality P847 FINISHED
Object Ocaña E685383 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: Ocaña | Statement: [Norte de Santander Department, hasMunicipality, Ocaña]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ocaña
Context triple: [Norte de Santander Department, hasMunicipality, Ocaña]
  • A. Ocaña chosen
    Ocaña is a historic city in northeastern Colombia known for its colonial architecture and role in the country’s independence-era events.
  • B. Peralillo
    Peralillo is a rural municipality and town in central Chile’s Colchagua wine-growing region, known for its agricultural production and vineyards.
  • C. Nalón
    The Nalón is a major river in Asturias, northern Spain, known for flowing through mountainous landscapes and historically supporting regional industry and mining.
  • D. Rabassa
    Rabassa is a surname most notably associated with Gregory Rabassa, the acclaimed American translator of Latin American literature.
  • E. Arganzuela
    Arganzuela is a central district of Madrid, Spain, known for its extensive redevelopment along the Manzanares River and its mix of residential areas, cultural venues, and green spaces.
  • 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_69c6995f9c60819092e386192bd63c6f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7035cddb881908bdfc1bd7d6a64ad completed March 27, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7c4482881908f7e763f019358cc completed March 29, 2026, 6:33 a.m.
Created at: March 27, 2026, 4:07 p.m.