Triple

T16105966
Position Surface form Disambiguated ID Type / Status
Subject Better Luck Tomorrow E390738 entity
Predicate screenwriter P2831 FINISHED
Object Fabienne Wen
Fabienne Wen is a screenwriter best known for co-writing the acclaimed indie crime drama film "Better Luck Tomorrow."
E1195150 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: Fabienne Wen | Statement: [Better Luck Tomorrow, screenwriter, Fabienne Wen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fabienne Wen
Context triple: [Better Luck Tomorrow, screenwriter, Fabienne Wen]
  • A. Simone Dienne
    Simone Dienne was the wife of French poet and screenwriter Jacques Prévert, known primarily through her association with his life and work.
  • B. Anne Dewavrin
    Anne Dewavrin is a French socialite known primarily for her past marriage to billionaire businessman Bernard Arnault, the chairman and CEO of LVMH.
  • C. Alexandra Lamy
    Alexandra Lamy is a French actress best known for her comedic roles in film and television, particularly the hit series "Un gars, une fille."
  • D. Stéphanie Von Euw
    Stéphanie Von Euw is a French politician who serves as the mayor of the city of Pontoise in the Île-de-France region.
  • E. Julie Le Brun
    Julie Le Brun was the daughter and frequent portrait subject of the renowned French painter Élisabeth Vigée Le Brun, often depicted in her mother's celebrated works.
  • 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: Fabienne Wen
Triple: [Better Luck Tomorrow, screenwriter, Fabienne Wen]
Generated description
Fabienne Wen is a screenwriter best known for co-writing the acclaimed indie crime drama film "Better Luck Tomorrow."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Fabienne Wen
Target entity description: Fabienne Wen is a screenwriter best known for co-writing the acclaimed indie crime drama film "Better Luck Tomorrow."
  • A. Simone Dienne
    Simone Dienne was the wife of French poet and screenwriter Jacques Prévert, known primarily through her association with his life and work.
  • B. Anne Dewavrin
    Anne Dewavrin is a French socialite known primarily for her past marriage to billionaire businessman Bernard Arnault, the chairman and CEO of LVMH.
  • C. Alexandra Lamy
    Alexandra Lamy is a French actress best known for her comedic roles in film and television, particularly the hit series "Un gars, une fille."
  • D. Stéphanie Von Euw
    Stéphanie Von Euw is a French politician who serves as the mayor of the city of Pontoise in the Île-de-France region.
  • E. Julie Le Brun
    Julie Le Brun was the daughter and frequent portrait subject of the renowned French painter Élisabeth Vigée Le Brun, often depicted in her mother's celebrated works.
  • 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_69d87f1a8dd881909f1de6ef78849874 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff6d81d081909e1315f4dbfd7369 completed April 17, 2026, 9:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeba1e4c08190a90f5102e0038056 completed May 10, 2026, 2:21 a.m.
NEDg Description generation batch_69ffed3d57388190a4d0faa58ee2a27b completed May 10, 2026, 2:28 a.m.
NED2 Entity disambiguation (via description) batch_69ffedfb88a881909e6adbb3a372246b completed May 10, 2026, 2:31 a.m.
Created at: April 10, 2026, 5 a.m.