Triple

T7702308
Position Surface form Disambiguated ID Type / Status
Subject Neiva E174528 entity
Predicate departmentCode P9698 FINISHED
Object Huila
Huila is a department in southwestern Colombia known for its coffee production, the Tatacoa Desert, and the Betania and El Quimbo hydroelectric reservoirs.
E682946 NE FINISHED

How this triple was built (4 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: Huila | Statement: [Neiva, departmentCode, Huila]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Huila
Context triple: [Neiva, departmentCode, Huila]
  • A. Espinal
    Espinal is a significant urban center in central Colombia known for its agricultural economy and cultural traditions within the Tolima Department.
  • B. Llanera
    Llanera is a rural municipality in the province of Nueva Ecija in the Philippines, known primarily for its agricultural economy and rice farming.
  • C. Bochica
    Bochica is a principal civilizing hero and culture god in Muisca mythology, associated with teaching laws, crafts, and moral order to the people.
  • D. Chinchiná
    Chinchiná is a Colombian town and municipality known for its coffee production and location in the central Andean region.
  • E. Sabaneta
    Sabaneta is a small but densely populated municipality in the Medellín metropolitan area of Colombia’s Aburrá Valley, known for its rapid urban growth and residential character.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Huila
Triple: [Neiva, departmentCode, Huila]
Generated description
Huila is a department in southwestern Colombia known for its coffee production, the Tatacoa Desert, and the Betania and El Quimbo hydroelectric reservoirs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Huila
Target entity description: Huila is a department in southwestern Colombia known for its coffee production, the Tatacoa Desert, and the Betania and El Quimbo hydroelectric reservoirs.
  • A. Espinal
    Espinal is a significant urban center in central Colombia known for its agricultural economy and cultural traditions within the Tolima Department.
  • B. Llanera
    Llanera is a rural municipality in the province of Nueva Ecija in the Philippines, known primarily for its agricultural economy and rice farming.
  • C. Bochica
    Bochica is a principal civilizing hero and culture god in Muisca mythology, associated with teaching laws, crafts, and moral order to the people.
  • D. Chinchiná
    Chinchiná is a Colombian town and municipality known for its coffee production and location in the central Andean region.
  • E. Sabaneta
    Sabaneta is a small but densely populated municipality in the Medellín metropolitan area of Colombia’s Aburrá Valley, known for its rapid urban growth and residential character.
  • F. None of above. chosen

Provenance (5 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_69c6995a72cc8190998e56daa6f8e453 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7028a2f9881908a2f1a257566fb7b completed March 27, 2026, 10:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8acbc2024819083576f5a11c1e3a8 completed March 29, 2026, 4:38 a.m.
NEDg Description generation batch_69c8adeb3948819087404b0d7d7e619e completed March 29, 2026, 4:43 a.m.
NED2 Entity disambiguation (via description) batch_69c8aedede388190b8eb79cea223c31c completed March 29, 2026, 4:47 a.m.
Created at: March 27, 2026, 4:03 p.m.