Triple

T36022526
Position Surface form Disambiguated ID Type / Status
Subject Prefeitura de Jundiaí E1042027 entity
Predicate governs P760 FINISHED
Object municipality of Jundiaí
The municipality of Jundiaí is a major urban and industrial center in the state of São Paulo, Brazil, known for its strong economy, quality of life, and strategic location between São Paulo and Campinas.
E2165311 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 Jundiaí | Statement: [Prefeitura de Jundiaí, governs, municipality of Jundiaí]
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 Jundiaí
Triple: [Prefeitura de Jundiaí, governs, municipality of Jundiaí]
Generated description
The municipality of Jundiaí is a major urban and industrial center in the state of São Paulo, Brazil, known for its strong economy, quality of life, and strategic location between São Paulo and Campinas.

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_69f76e2c568881909e1e21f85252b0f0 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ace4902c8190b4f60da85030a47e completed May 3, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38c002095c819089d809bd3272386a completed June 22, 2026, 4:54 a.m.
NEDg Description generation batch_6a38c0a93ce881908c7f774b519e5247 completed June 22, 2026, 4:57 a.m.
NED2 Entity disambiguation (via description) batch_6a38c14a3b6c81908d6bcb4ed8316a28 completed June 22, 2026, 4:59 a.m.
Created at: May 3, 2026, 4:07 p.m.