Triple

T26769895
Position Surface form Disambiguated ID Type / Status
Subject Historic City of Sucre E675048 entity
Predicate governingBody P46 FINISHED
Object Municipality of Sucre
The Municipality of Sucre is the local government authority responsible for administering the city of Sucre, Bolivia’s constitutional capital and a UNESCO-listed historic city.
E1739788 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 Sucre | Statement: [Historic City of Sucre, governingBody, Municipality of Sucre]
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 Sucre
Triple: [Historic City of Sucre, governingBody, Municipality of Sucre]
Generated description
The Municipality of Sucre is the local government authority responsible for administering the city of Sucre, Bolivia’s constitutional capital and a UNESCO-listed historic city.

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_69eecda85298819097ee1c38a3d772e7 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6192c45fc819094e7dd70fd9cc333 completed May 2, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a120952e43c8190a888dedd18d350c3 completed May 23, 2026, 8:08 p.m.
NEDg Description generation batch_6a1209bac5dc8190a3a0bcd25dc6f9c4 completed May 23, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_6a120a7acb6081909b538b1a351a92bd completed May 23, 2026, 8:13 p.m.
Created at: April 27, 2026, 4:01 a.m.