Triple

T3595099
Position Surface form Disambiguated ID Type / Status
Subject Fernand Khnopff E76118 entity
Predicate givenName P17 FINISHED
Object Fernand E338517 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: Fernand | Statement: [Fernand Khnopff, givenName, Fernand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fernand
Context triple: [Fernand Khnopff, givenName, Fernand]
  • A. Fernand chosen
    Fernand is a given name, primarily used in French and other Romance-language contexts, that corresponds to the name Ferdinand.
  • B. Pierre
    Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
  • C. René
    René is a French given name commonly used for males and historically associated with several notable figures in politics, arts, and philosophy.
  • 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. Léon Marchal
    Léon Marchal was a French diplomat who served as Secretary General of the Council of Europe during the early years of European postwar integration.
  • 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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc15f41cc819085b3e897d823757d completed March 8, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5336104a081908c5f07e8b4d22c58 completed March 14, 2026, 10:07 a.m.
Created at: March 8, 2026, 3:22 p.m.