Triple

T33157647
Position Surface form Disambiguated ID Type / Status
Subject Marie Dubois E848626 entity
Predicate alsoKnownAs P39 FINISHED
Object Claudine Huzé
Claudine Huzé, better known by her stage name Marie Dubois, was a French actress recognized for her roles in New Wave cinema and popular French films of the 1960s and 1970s.
E2223273 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: Claudine Huzé | Statement: [Marie Dubois, alsoKnownAs, Claudine Huzé]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Claudine Huzé
Triple: [Marie Dubois, alsoKnownAs, Claudine Huzé]
Generated description
Claudine Huzé, better known by her stage name Marie Dubois, was a French actress recognized for her roles in New Wave cinema and popular French films of the 1960s and 1970s.

Provenance (5 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_69f3495b02d08190bb3d366823dffc21 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d8ee10b0819084f6aba7f1033b95 completed May 3, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a406cb47048819096c51142ec6deee5 completed June 28, 2026, 12:37 a.m.
NEDg Description generation batch_6a406db565b881909769124848e2b508 completed June 28, 2026, 12:41 a.m.
NED2 Entity disambiguation (via description) batch_6a406e2e5e00819097b90719f08951c8 completed June 28, 2026, 12:43 a.m.
Created at: May 1, 2026, 1:28 a.m.