Triple

T8111980
Position Surface form Disambiguated ID Type / Status
Subject Palestina, Caldas E189375 entity
Predicate roadAccessTo P22549 FINISHED
Object Chinchiná E195922 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: Chinchiná | Statement: [Palestina, Caldas, roadAccessTo, Chinchiná]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chinchiná
Context triple: [Palestina, Caldas, roadAccessTo, Chinchiná]
  • A. Chinchiná chosen
    Chinchiná is a Colombian town and municipality known for its coffee production and location in the central Andean region.
  • B. Colombia
    Colombia is a transcontinental country in northern South America, known for its diverse landscapes from Andes mountains to Amazon rainforest, rich cultural heritage, and major cities like Bogotá and Medellín.
  • C. Colombia
    Colombia is a station on Madrid's Metro network, serving Line 8 and acting as an important interchange point in the city's public transportation system.
  • D. Tocaima
    Tocaima is a historic Colombian town in the Cundinamarca Department, known for its warm climate and thermal springs.
  • E. Columbio
    Columbio is a rural municipality in the province of Sultan Kudarat in the Philippines, known for its agricultural economy and multicultural indigenous communities.
  • 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_69ca82baad008190ab2859712b9b1607 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb432bcb648190b5ddbcc2a3dbc9b1 completed March 31, 2026, 3:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc942a9af881908b7ddc724755893e completed April 1, 2026, 3:42 a.m.
Created at: March 30, 2026, 5:32 p.m.