Triple

T5847936
Position Surface form Disambiguated ID Type / Status
Subject Jean-Baptiste Darlan E129757 entity
Predicate familyName P18 FINISHED
Object Darlan E126474 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: Darlan | Statement: [Jean-Baptiste Darlan, familyName, Darlan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Darlan
Context triple: [Jean-Baptiste Darlan, familyName, Darlan]
  • A. Darlan chosen
    Darlan is a French surname most notably associated with François Darlan, a prominent admiral and political figure in Vichy France during World War II.
  • B. Carlos Lemos
    Carlos Lemos was a Brazilian architect known for his work on prominent modernist projects such as São Paulo’s iconic Copan Building.
  • C. Fernando Cayo
    Fernando Cayo is a Spanish film, television, and stage actor known internationally for roles in works such as the horror film "The Orphanage" and the series "Money Heist."
  • D. Bruno Barreto
    Bruno Barreto is a Brazilian film director known for works such as "Dona Flor and Her Two Husbands" and "Four Days in September."
  • E. Marcelo
    Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
  • 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_69c0084bd31c8190a796bb6284845e83 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03512d3548190920ac882189500d9 completed March 22, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a1ad4d888190b4a1e605887b2e2c completed March 23, 2026, 2:13 a.m.
Created at: March 22, 2026, 3:55 p.m.