Triple

T25119030
Position Surface form Disambiguated ID Type / Status
Subject Ichilo Province E629217 entity
Predicate hasMunicipality P847 FINISHED
Object Puerto Villarroel Municipality
Puerto Villarroel Municipality is an administrative municipality in central Bolivia, located within the tropical lowlands of Cochabamba Department’s Ichilo Province.
E1666132 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: Puerto Villarroel Municipality | Statement: [Ichilo Province, hasMunicipality, Puerto Villarroel 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: Puerto Villarroel Municipality
Triple: [Ichilo Province, hasMunicipality, Puerto Villarroel Municipality]
Generated description
Puerto Villarroel Municipality is an administrative municipality in central Bolivia, located within the tropical lowlands of Cochabamba Department’s Ichilo Province.

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_69e2ff3288048190bd82c3b7f7bd0e62 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f465c9bad88190b1488ada06e9b51b completed May 1, 2026, 8:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105cf6a4c08190a21b63f6537a2cdf completed May 22, 2026, 1:41 p.m.
NEDg Description generation batch_6a105dd12cd08190b382c57952107fa6 completed May 22, 2026, 1:44 p.m.
NED2 Entity disambiguation (via description) batch_6a105ed8d78c81908eb3648c65de38b1 completed May 22, 2026, 1:49 p.m.
Created at: April 18, 2026, 6:27 a.m.