Triple

T10205463
Position Surface form Disambiguated ID Type / Status
Subject Juliette Gréco E242180 entity
Predicate givenName P17 FINISHED
Object Juliette E265942 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: Juliette | Statement: [Juliette Gréco, givenName, Juliette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Juliette
Context triple: [Juliette Gréco, givenName, Juliette]
  • A. Juliette chosen
    Juliette is a feminine given name of French origin, widely used in many countries and popularized through literature and film.
  • B. Julietta
    Julietta is a surreal three-act opera by Czech composer Bohuslav Martinů, based on Georges Neveux’s play about a man searching for a woman in a dreamlike town where people have lost their memories.
  • C. Juliette Welfling
    Juliette Welfling is a French film editor known for her work on numerous acclaimed international films, including the heist movie "Ocean's 8."
  • D. Laetitia
    Laetitia is a feminine given name of Latin origin, historically borne by figures such as the English poet and essayist Anna Laetitia Barbauld.
  • E. Émilie
    Émilie is the given first name of the French-born American actress Claudette Colbert, a major Hollywood star of the 1930s and 1940s.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d395f6298c8190a4a0ad9770f10e80 completed April 6, 2026, 11:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d652b489608190b844e1199e6126ce completed April 8, 2026, 1:05 p.m.
Created at: April 6, 2026, 10:44 a.m.