Triple
T17024282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Police Story |
E413023
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Brigitte Lin |
E747641
|
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: Brigitte Lin | Statement: [Police Story, starring, Brigitte Lin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brigitte Lin Context triple: [Police Story, starring, Brigitte Lin]
-
A.
Brigitte Lin
chosen
Brigitte Lin is a celebrated Taiwanese actress best known internationally for her iconic roles in 1980s–1990s Hong Kong cinema, including acclaimed collaborations with auteur directors such as Wong Kar-wai.
-
B.
Rita Hsiao
Rita Hsiao is a screenwriter best known for her work on animated feature films, including co-writing Pixar's "Toy Story 2."
-
C.
Yvonne Jung
Yvonne Jung is an American actress known for her work in film and television, including roles in crime dramas and independent movies.
-
D.
Estella Kwan
Estella Kwan is the mother of American figure skating champion Michelle Wingshan Kwan.
-
E.
Nancy Kwan
Nancy Kwan is a pioneering Hong Kong–born actress who became an international star in the 1960s and a trailblazer for Asian representation in Hollywood and global cinema.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d371148190a60d32a72abec09a |
completed | April 18, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b514de481909c78c17a3014b468 |
completed | May 10, 2026, 11:57 p.m. |
Created at: April 10, 2026, 5:33 a.m.