Triple

T11911861
Position Surface form Disambiguated ID Type / Status
Subject Barueri E283414 entity
Predicate hasNeighbour P5707 FINISHED
Object Itapevi E293514 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: Itapevi | Statement: [Barueri, hasNeighbour, Itapevi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Itapevi
Context triple: [Barueri, hasNeighbour, Itapevi]
  • A. Itapevi chosen
    Itapevi is a municipality in the metropolitan region of São Paulo, Brazil, known for its growing industrial sector and residential expansion.
  • B. Itapura
    Itapura is a municipality in the state of São Paulo, Brazil, located on the banks of the Tietê River near its confluence with the Paraná River.
  • C. Combarbalá
    Combarbalá is a small Chilean town and municipality in the Coquimbo Region, known for its semi-arid landscapes, goat farming, and distinctive combarbalite stone crafts.
  • D. Icó
    Icó is a historic municipality in northeastern Brazil known for its colonial architecture and cultural heritage within the state of Ceará.
  • E. Piaçabuçu
    Piaçabuçu is a coastal municipality in the Brazilian state of Alagoas known for its scenic dunes, beaches, and proximity to the mouth of the São Francisco River.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e528f6748190ac873a040a61fa93 completed April 10, 2026, 11:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69f44014e1d08190ac7425f375ca023f completed May 1, 2026, 5:54 a.m.
Created at: April 8, 2026, 9:44 p.m.