Triple

T10128928
Position Surface form Disambiguated ID Type / Status
Subject Bogotá River E226284 entity
Predicate passesNear P416 FINISHED
Object Villeta E31476 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: Villeta | Statement: [Bogotá River, passesNear, Villeta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Villeta
Context triple: [Bogotá River, passesNear, Villeta]
  • A. Villeta chosen
    Villeta is a Colombian town and municipality in the department of Cundinamarca, known for its warm climate and sugarcane production.
  • B. Villa
    Villa is a shorthand name commonly used to refer to Aston Villa Football Club, a historic English professional football team based in Birmingham.
  • C. Villete
    Villete is a fictional town in Charlotte Brontë’s novel of the same name, serving as the atmospheric setting for Lucy Snowe’s experiences in a girls’ boarding school.
  • D. Villa Alegre
    Villa Alegre is a small rural municipality in Chile’s Maule Region, known for its agricultural activity and traditional central valley landscapes.
  • E. Villa Carlos
    Villa Carlos is the former historical name of the town now known as Es Castell, located on the island of Menorca in Spain.
  • 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd333186c819088bbf617967f24fa completed April 2, 2026, 2:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cc72848481909dcbfc9fe3f6d379 completed April 5, 2026, 8:56 p.m.
Created at: March 30, 2026, 9:05 p.m.