Triple

T24336155
Position Surface form Disambiguated ID Type / Status
Subject Sacaba E613386 entity
Predicate administrativeDivisionOf P747 FINISHED
Object Sacaba Municipality
Sacaba Municipality is a local government area in the Cochabamba Department of Bolivia that encompasses the city of Sacaba and its surrounding communities.
E1639907 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: Sacaba Municipality | Statement: [Sacaba, administrativeDivisionOf, Sacaba Municipality]
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: Sacaba Municipality
Triple: [Sacaba, administrativeDivisionOf, Sacaba Municipality]
Generated description
Sacaba Municipality is a local government area in the Cochabamba Department of Bolivia that encompasses the city of Sacaba and its surrounding communities.

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_69e2d7dcc5a08190b53691130d56cbc4 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292f5346881909ca93b7ceef543ed completed April 29, 2026, 11:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee5d2a34819083e3a746add1d1f6 completed May 22, 2026, 5:49 a.m.
NEDg Description generation batch_6a0ff29929888190a0e759d3e58affc9 completed May 22, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff2f5ec608190a63d692c10908ee9 completed May 22, 2026, 6:08 a.m.
Created at: April 18, 2026, 1:56 a.m.