Triple

T12460760
Position Surface form Disambiguated ID Type / Status
Subject John Gaw Meem E297784 entity
Predicate placeOfBirth P1 FINISHED
Object Pelotas, Brazil E656524 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: Pelotas, Brazil | Statement: [John Gaw Meem, placeOfBirth, Pelotas, Brazil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pelotas, Brazil
Context triple: [John Gaw Meem, placeOfBirth, Pelotas, Brazil]
  • A. Pelotas chosen
    Pelotas is a historic city in southern Brazil known for its colonial architecture, cultural festivals, and traditional sweets industry.
  • B. Bento Gonçalves, Brazil
    Bento Gonçalves is a city in Brazil’s southern state of Rio Grande do Sul, known for its Italian heritage and as a major center of the country’s wine production.
  • C. Santos city
    Santos city is a coastal municipality in the state of São Paulo, Brazil, best known for its major port and its historic football club Santos FC.
  • D. Canoas
    Canoas is a major industrial and residential city in the Porto Alegre metropolitan region of Rio Grande do Sul, Brazil.
  • E. Jaraguá do Sul
    Jaraguá do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage and industrial economy.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94db465c48190bcfaf22f25ef8947 completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f1d4f248190a0805e17da42eaf7 completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:56 p.m.