Triple

T18653391
Position Surface form Disambiguated ID Type / Status
Subject Pierre André de Suffren E455997 entity
Predicate givenName P17 FINISHED
Object André NE NERFINISHED

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: André | Statement: [Pierre André de Suffren, givenName, André]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: André
Context triple: [Pierre André de Suffren, givenName, André]
  • A. André chosen
    André is a given name of French origin commonly used in various languages as a form of "Andrew."
  • B. André David
    André David was one of the discoverers of the prehistoric painted cave of Pech Merle in southwestern France.
  • C. André Pascal
    André Pascal was a notable French figure, likely a politician or public servant, after whom Rue André Pascal in Paris is named.
  • D. Hervé
    Hervé is a French given name, often considered a variant of the English name Harvey, and is commonly used for males in French-speaking regions.
  • E. André Daina
    André Daina is a Swiss former football referee best known for officiating major European club competitions in the 1980s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38ea1e88190997e9b231190ba6f completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55013997881909eee52c0a7335f4b completed April 19, 2026, 9:58 p.m.
Created at: April 10, 2026, 11:47 a.m.