Triple

T2720757
Position Surface form Disambiguated ID Type / Status
Subject CPTM commuter rail E60073 entity
Predicate connectsMunicipality P4245 FINISHED
Object Mauá E293505 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: Mauá | Statement: [CPTM commuter rail, connectsMunicipality, Mauá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mauá
Context triple: [CPTM commuter rail, connectsMunicipality, Mauá]
  • A. Mauá chosen
    Mauá is an industrial and residential city located in the metropolitan region of São Paulo, Brazil.
  • B. Panarima
    Panarima is a musical track featured on the album "Legend of the Sun Virgin."
  • C. Caicó
    Caicó is a municipality in the interior of Rio Grande do Norte, Brazil, known for its strong cultural traditions, especially its famous religious festivals and regional cuisine.
  • D. Alcântara
    Alcântara is a historic coastal municipality in the Brazilian state of Maranhão, known for its preserved colonial architecture and proximity to the Alcântara Launch Center.
  • E. Corumbá
    Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
  • 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_69ab4b746d248190958e052045c09255 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd1fc30c81909ac06588d50abdf8 completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8920e64819099074f019020bb59 completed March 10, 2026, 9:46 a.m.
Created at: March 6, 2026, 9:55 p.m.