Triple

T239336
Position Surface form Disambiguated ID Type / Status
Subject Cundinamarca Department E4892 entity
Predicate contains P35 FINISHED
Object Suesca E41567 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: Suesca | Statement: [Cundinamarca Department, contains, Suesca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suesca
Context triple: [Cundinamarca Department, contains, Suesca]
  • A. Suesca chosen
    Suesca is a Colombian town in the department of Cundinamarca, renowned for its dramatic rock cliffs that make it a popular destination for rock climbing and outdoor recreation.
  • B. Soacha
    Soacha is a rapidly growing industrial and residential city in central Colombia, located just southwest of Bogotá in the department of Cundinamarca.
  • C. Cajicá
    Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
  • D. Fusagasugá
    Fusagasugá is a Colombian city in the department of Cundinamarca, known for its mild climate, flower cultivation, and role as an important commercial and agricultural center near Bogotá.
  • E. Villapinzón
    Villapinzón is a Colombian town and municipality in the department of Cundinamarca, known for its leather industry and location in the Andean highlands.
  • 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_69a257c3d0708190b0871c4269d273e6 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25ceaecdc81909e9ff49cb6a4e02a completed Feb. 28, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3e85c6c008190a9500b4876a78661 completed March 1, 2026, 7:18 a.m.
Created at: Feb. 28, 2026, 2:53 a.m.