Triple

T26015557
Position Surface form Disambiguated ID Type / Status
Subject Minister of Health and Social Protection of Colombia E647012 entity
Predicate positionHeldBy P8 FINISHED
Object Juan Pablo Uribe
Juan Pablo Uribe is a Colombian physician and public health expert who has served as the country’s Minister of Health and Social Protection.
E1716476 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: Juan Pablo Uribe | Statement: [Minister of Health and Social Protection of Colombia, positionHeldBy, Juan Pablo Uribe]
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: Juan Pablo Uribe
Triple: [Minister of Health and Social Protection of Colombia, positionHeldBy, Juan Pablo Uribe]
Generated description
Juan Pablo Uribe is a Colombian physician and public health expert who has served as the country’s Minister of Health and Social Protection.

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_69e77e8aa65881909ca58918f29ab2a0 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f605b8bea081909174b814049480e6 completed May 2, 2026, 2:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11855a4ca88190be46584287585edf completed May 23, 2026, 10:45 a.m.
NEDg Description generation batch_6a118930b3308190837af6a5b703c4a5 completed May 23, 2026, 11:02 a.m.
NED2 Entity disambiguation (via description) batch_6a1189dcc1348190b1318d89e9d24fb9 completed May 23, 2026, 11:05 a.m.
Created at: April 22, 2026, 9:03 a.m.