Triple

T10505933
Position Surface form Disambiguated ID Type / Status
Subject Graça Machel E247786 entity
Predicate givenName P17 FINISHED
Object Graça E108959 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: Graça | Statement: [Graça Machel, givenName, Graça]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Graça
Context triple: [Graça Machel, givenName, Graça]
  • A. Graça chosen
    Graça is a historic hilltop neighborhood in Lisbon, Portugal, known for its traditional streets, viewpoints over the city, and classic tram connections.
  • B. Redenção
    Redenção is a municipality in the state of Ceará, Brazil, known historically as one of the first Brazilian cities to abolish slavery.
  • C. Chiado
    Chiado is a historic and upscale neighborhood in central Lisbon known for its elegant shops, cafés, theaters, and literary heritage.
  • D. Campoalegre
    Campoalegre is a municipality and town in southwestern Colombia, located in the Huila Department and known for its agricultural production.
  • E. Nilópolis
    Nilópolis is a densely populated municipality in the state of Rio de Janeiro, Brazil, known for its urban character and strong cultural ties to the Rio de Janeiro metropolitan area.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509a07c908190bf0e3e5d480b306d completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dce30d788190b4a40340b9200b10 completed April 10, 2026, 11:20 a.m.
Created at: April 6, 2026, 12:26 p.m.