Triple

T3460469
Position Surface form Disambiguated ID Type / Status
Subject The Book of Boba Fett E73010 entity
Predicate starring P1507 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: [The Book of Boba Fett, starring, Ming-Na Wen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ming-Na Wen
Context triple: [The Book of Boba Fett, starring, 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. Bai Ling
    Bai Ling is a Chinese-American actress known for her eccentric persona and roles in films such as "The Crow," "Red Corner," and various independent and genre movies.
  • 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_69ad85b224d481908ff8be51338d24ff completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbae5ff848190880fa416a123bc4a completed March 8, 2026, 6:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69b361093d288190a023e8485265a989 completed March 13, 2026, 12:57 a.m.
Created at: March 8, 2026, 3:17 p.m.