Triple

T10340214
Position Surface form Disambiguated ID Type / Status
Subject Bob Rafelson E243107 entity
Predicate spouse P13 FINISHED
Object Gabrielle Taurek
Gabrielle Taurek is an American actress and producer best known for her work in independent films and her long-term partnership with filmmaker Bob Rafelson.
E858258 NE FINISHED

How this triple was built (4 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: Gabrielle Taurek | Statement: [Bob Rafelson, spouse, Gabrielle Taurek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gabrielle Taurek
Context triple: [Bob Rafelson, spouse, Gabrielle Taurek]
  • A. Gabrielle Tana
    Gabrielle Tana is a British film producer known for acclaimed dramas such as "Philomena" and other prestige, character-driven films.
  • B. Gabrielle Starr
    Gabrielle Starr is an American literary scholar and academic administrator who serves as the president of Pomona College.
  • C. Gabrielle Gerard
    Gabrielle Gerard is the principal female character in the classic MGM musical film "The Band Wagon," portrayed as a talented ballerina and Fred Astaire’s romantic and dance partner.
  • D. Gabrielle Glore
    Gabrielle Glore is a film producer best known for her work on the romantic drama "Sylvie’s Love."
  • E. Gabrielle Stone
    Gabrielle Stone is an American actress and author, known for her work in independent films and for writing the bestselling memoir "Eat, Pray, #FML."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Gabrielle Taurek
Triple: [Bob Rafelson, spouse, Gabrielle Taurek]
Generated description
Gabrielle Taurek is an American actress and producer best known for her work in independent films and her long-term partnership with filmmaker Bob Rafelson.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gabrielle Taurek
Target entity description: Gabrielle Taurek is an American actress and producer best known for her work in independent films and her long-term partnership with filmmaker Bob Rafelson.
  • A. Gabrielle Tana
    Gabrielle Tana is a British film producer known for acclaimed dramas such as "Philomena" and other prestige, character-driven films.
  • B. Gabrielle Starr
    Gabrielle Starr is an American literary scholar and academic administrator who serves as the president of Pomona College.
  • C. Gabrielle Gerard
    Gabrielle Gerard is the principal female character in the classic MGM musical film "The Band Wagon," portrayed as a talented ballerina and Fred Astaire’s romantic and dance partner.
  • D. Gabrielle Glore
    Gabrielle Glore is a film producer best known for her work on the romantic drama "Sylvie’s Love."
  • E. Gabrielle Stone
    Gabrielle Stone is an American actress and author, known for her work in independent films and for writing the bestselling memoir "Eat, Pray, #FML."
  • F. None of above. chosen

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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e0a526a08190afe7091a0cf1f073 completed April 7, 2026, 10:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7506a07888190b91e78247e81fe57 completed April 9, 2026, 7:08 a.m.
NEDg Description generation batch_69d7618c9abc819080c4d6669dfb8320 completed April 9, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69d7702ae24481908b0f5319413e81d4 completed April 9, 2026, 9:23 a.m.
Created at: April 6, 2026, 11:54 a.m.