Triple
T15312493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Knights |
E366071
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Willie Chan |
E1151286
|
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: Willie Chan | Statement: [Shanghai Knights, producer, Willie Chan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willie Chan Context triple: [Shanghai Knights, producer, Willie Chan]
-
A.
Willie Chan
chosen
Willie Chan was a prominent Hong Kong film producer and talent manager best known for his long-time collaboration with Jackie Chan and his influential role in the Hong Kong action cinema industry.
-
B.
Ronnie Chan
Ronnie Chan is a Hong Kong billionaire businessman and philanthropist best known as the chairman of Hang Lung Group and for his prominent role in property development and higher-education philanthropy.
-
C.
Ryan Chan
Ryan Chan is a film editor known for his work on the 2020 adaptation of "The Witches."
-
D.
Ling Woo
Ling Woo is a sharp-tongued, unapologetically confident attorney on the television series "Ally McBeal," known for her icy demeanor, wit, and complex relationship dynamics.
-
E.
Peter Kwong
Peter Kwong is an American character actor best known for his roles in genre films and television, including cult favorites from the 1980s and 1990s.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03cd2d5a88190aead748920f93d47 |
completed | April 16, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2cea6bb88190a6d6f7c55daa4677 |
completed | May 9, 2026, 12:47 p.m. |
Created at: April 10, 2026, 3:16 a.m.