Triple

T34743622
Position Surface form Disambiguated ID Type / Status
Subject Nazaré Paulista E1001572 entity
Predicate locatedNear P294 FINISHED
Object Bom Jesus dos Perdões
Bom Jesus dos Perdões is a small municipality in the state of São Paulo, Brazil, known for its religious traditions and proximity to the Cantareira mountain region.
E2111069 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: Bom Jesus dos Perdões | Statement: [Nazaré Paulista, locatedNear, Bom Jesus dos Perdões]
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: Bom Jesus dos Perdões
Triple: [Nazaré Paulista, locatedNear, Bom Jesus dos Perdões]
Generated description
Bom Jesus dos Perdões is a small municipality in the state of São Paulo, Brazil, known for its religious traditions and proximity to the Cantareira mountain region.

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_69f76db0367081909b57c50a7fb03025 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f779d10d548190b7e1efddf620503b completed May 3, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37662a79fc8190a7df1f1584d76ec5 completed June 21, 2026, 4:18 a.m.
NEDg Description generation batch_6a376816f01881909583a8b9f814e905 completed June 21, 2026, 4:27 a.m.
NED2 Entity disambiguation (via description) batch_6a37687fabdc81908d7ed5f0e0f1903b completed June 21, 2026, 4:28 a.m.
Created at: May 3, 2026, 3:59 p.m.