Triple

T3137764
Position Surface form Disambiguated ID Type / Status
Subject Laurent Schwartz E65574 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 Schwartz, givenName, Laurent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laurent
Context triple: [Laurent Schwartz, 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. Benoît
    Benoît is the French form of the given name Benedict, commonly used in French-speaking countries.
  • C. Étienne
    Étienne is the given first name of the French Symbolist poet Stéphane Mallarmé.
  • D. 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.
  • E. Lucien
    Lucien is a masculine given name of Latin origin, historically associated with figures such as Lucien Bonaparte, the brother of Napoleon Bonaparte.
  • 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_69ad8581c25c8190b0d85ba9b9baa531 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada574509c81908a88bb10ea35516d completed March 8, 2026, 4:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b324e2f1448190be5b744abdeed314 completed March 12, 2026, 8:41 p.m.
Created at: March 8, 2026, 3:05 p.m.