Triple

T12489485
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan Region of Campinas E298523 entity
Predicate hasMunicipality P847 FINISHED
Object Monte Mor E1001455 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: Monte Mor | Statement: [Metropolitan Region of Campinas, hasMunicipality, Monte Mor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monte Mor
Context triple: [Metropolitan Region of Campinas, hasMunicipality, Monte Mor]
  • A. Monte Mor chosen
    Monte Mor is a municipality in the state of São Paulo, Brazil, known for its role in the Campinas metropolitan region and its growing industrial and residential development.
  • B. Monte Brown
    Monte Brown is a musician best known for his work with the new wave band Tom Tom Club.
  • C. Monte Blue
    Monte Blue was an American film actor prominent during the silent era and early sound period, known for his leading and character roles in numerous Hollywood productions.
  • D. Monte Markham
    Monte Markham is an American actor and producer known for his extensive work in television and film since the 1960s, including roles in series such as "Barnaby Jones" and "Baywatch."
  • E. Mount Serra
    Mount Serra is a geographical feature in Liberia that lent its name to Montserrado County, one of the country’s key administrative regions.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94de1db9481909ddf70eb81cdb714 completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ea59d20819099021f36fc430856 completed May 2, 2026, 11:54 p.m.
Created at: April 8, 2026, 9:56 p.m.