Triple

T8089086
Position Surface form Disambiguated ID Type / Status
Subject Departamento de Casanare E188808 entity
Predicate hasMunicipality P847 FINISHED
Object Nunchía E658154 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: Nunchía | Statement: [Departamento de Casanare, hasMunicipality, Nunchía]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nunchía
Context triple: [Departamento de Casanare, hasMunicipality, Nunchía]
  • A. Nunchía chosen
    Nunchía is a municipality in eastern Colombia known for its rural landscapes and cattle-ranching traditions within the Casanare region of the Llanos.
  • B. Punasa
    Punasa is a town in Madhya Pradesh, India, known for its proximity to the major Indira Sagar Dam on the Narmada River.
  • C. Nasuella
    Nasuella is a small genus of South American carnivorous mammals known as mountain coatis, characterized by their elongated snouts and arboreal habits.
  • D. Kulisusu
    Kulisusu is a town and administrative center located in the province of Southeast Sulawesi, Indonesia.
  • E. Chigorodó
    Chigorodó is a municipality in Colombia’s Antioquia Department, known for its agricultural production and location in the Urabá region.
  • 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_69ca82b7b3e88190b9041ab0ef28b3cb completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb421c717c819089dd88c30a6401aa completed March 31, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc640a42648190bc1a3072eb338e22 completed April 1, 2026, 12:17 a.m.
Created at: March 30, 2026, 5:29 p.m.