Triple

T10568520
Position Surface form Disambiguated ID Type / Status
Subject Eugène Beaudouin E249415 entity
Predicate givenName P17 FINISHED
Object Eugène E40593 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: Eugène | Statement: [Eugène Beaudouin, givenName, Eugène]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eugène
Context triple: [Eugène Beaudouin, givenName, Eugène]
  • A. Eugène chosen
    Eugène is a masculine given name of French origin, derived from the Greek "Eugenios," meaning "well-born" or "noble."
  • 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. Gustave
    Gustave is a masculine given name of French origin, famously borne by engineer Gustave Eiffel.
  • E. Théodore
    Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5272ff53c8190ae7c399d49b585f5 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d97a10f17081909fd9465cf35685a1 completed April 10, 2026, 10:30 p.m.
Created at: April 6, 2026, 12:37 p.m.