Triple

T4819038
Position Surface form Disambiguated ID Type / Status
Subject Laurent of Belgium E107662 entity
Predicate givenName P17 FINISHED
Object Laurent E107662 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: Laurent | Statement: [Laurent of Belgium, givenName, Laurent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laurent
Context triple: [Laurent of Belgium, givenName, Laurent]
  • A. Laurent chosen
    Laurent is a Belgian prince, the younger son of King Albert II and Queen Paola, known for his environmental interests and occasional public controversies.
  • B. Laurent
    Laurent is a central figure in Émile Zola’s novel "Thérèse Raquin," known as Thérèse’s lover and accomplice in a dark, psychologically driven crime.
  • C. Benoît
    Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
  • D. Étienne
    Étienne is the given first name of the French Symbolist poet Stéphane Mallarmé.
  • E. Firmin
    Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
  • 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_69bd43f9efa081908314cb3e94fa1695 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6c96f4dc81909e3186159b5c75ab completed March 20, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67ce5808819093004d4ed42ed211 completed March 21, 2026, 9:41 a.m.
Created at: March 20, 2026, 1:24 p.m.