Triple

T27263833
Position Surface form Disambiguated ID Type / Status
Subject Ituango E687841 entity
Predicate borderedBy P224 FINISHED
Object municipality of Dabeiba
The municipality of Dabeiba is a rural Andean locality in the Antioquia Department of Colombia, known for its mountainous terrain, biodiversity, and history marked by armed conflict and subsequent peacebuilding efforts.
E1762764 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: municipality of Dabeiba | Statement: [Ituango, borderedBy, municipality of Dabeiba]
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: municipality of Dabeiba
Triple: [Ituango, borderedBy, municipality of Dabeiba]
Generated description
The municipality of Dabeiba is a rural Andean locality in the Antioquia Department of Colombia, known for its mountainous terrain, biodiversity, and history marked by armed conflict and subsequent peacebuilding efforts.

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_69ef3557abc481908bf3c146f0f3356a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f626f1fcec81909c542acb032e81fb completed May 2, 2026, 4:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a126287a38081909c63fbe3c0bbbbea completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a1263c16b7c8190bf1e6d9a48f04e79 completed May 24, 2026, 2:34 a.m.
NED2 Entity disambiguation (via description) batch_6a12645e001081909536516633a422a9 completed May 24, 2026, 2:37 a.m.
Created at: April 27, 2026, 10:54 a.m.