Triple

T3826744
Position Surface form Disambiguated ID Type / Status
Subject Chinese American cinema E88707 entity
Predicate notableActor P7010 FINISHED
Object Ming-Na Wen E343851 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: Ming-Na Wen | Statement: [Chinese American cinema, notableActor, Ming-Na Wen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ming-Na Wen
Context triple: [Chinese American cinema, notableActor, Ming-Na Wen]
  • A. Ming-Na Wen chosen
    Ming-Na Wen is a Chinese-American actress best known for her roles in projects like ER, Agents of S.H.I.E.L.D., and various Disney productions.
  • B. Zoë Chao
    Zoë Chao is an American actress and writer known for her work in film and television, including prominent roles in indie comedies and streaming series.
  • C. Lucy Liu
    Lucy Liu is an American actress and producer known for her versatile roles in film and television, including standout performances in projects like "Ally McBeal," "Kill Bill," and "Elementary."
  • D. Rita Hsiao
    Rita Hsiao is a screenwriter best known for her work on animated feature films, including co-writing Pixar's "Toy Story 2."
  • E. Nia Long
    Nia Long is an American actress known for her roles in films like "Boyz n the Hood," "Love Jones," and "The Best Man," as well as the TV series "The Fresh Prince of Bel-Air."
  • 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_69aed9538cf881909d9ce8ca4ac7c18c completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeeb64c72c8190b5f3d376aa4ee933 completed March 9, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4fb4f41c88190b3040236462c37cc completed March 14, 2026, 6:08 a.m.
Created at: March 9, 2026, 3:17 p.m.