Triple

T27262929
Position Surface form Disambiguated ID Type / Status
Subject Magdalena Medio Santander E687815 entity
Predicate containsMunicipality P852 FINISHED
Object Betulia
Betulia is a rural municipality in the Santander Department of Colombia, known for its agricultural economy and location within the Magdalena Medio region.
E1762748 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: Betulia | Statement: [Magdalena Medio Santander, containsMunicipality, Betulia]
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: Betulia
Triple: [Magdalena Medio Santander, containsMunicipality, Betulia]
Generated description
Betulia is a rural municipality in the Santander Department of Colombia, known for its agricultural economy and location within the Magdalena Medio region.

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_69f626f07218819080448c001f01ba45 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.