Triple
T17024482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Police Story 3: Supercop |
E413027
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Fong Chi-keung |
E1257965
|
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: Fong Chi-keung | Statement: [Police Story 3: Supercop, screenwriter, Fong Chi-keung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fong Chi-keung Context triple: [Police Story 3: Supercop, screenwriter, Fong Chi-keung]
-
A.
Fong Chi-keung
chosen
Fong Chi-keung is a Hong Kong screenwriter best known for his work on action films, including the Jackie Chan hit "Rumble in the Bronx."
-
B.
Chow Shiu-hung
Chow Shiu-hung is an individual notable for bearing the Chinese surname Chow, recognized in records of people with this family name.
-
C.
Yuen Siu-tien
Yuen Siu-tien was a Hong Kong martial arts film actor best known for his iconic portrayal of the drunken master Beggar So in classic kung fu cinema.
-
D.
Yam Kim-fai
Yam Kim-fai was a legendary Cantonese opera star renowned for her charismatic male "sheng" roles and lasting influence on Hong Kong’s performing arts.
-
E.
Lok Fu
Lok Fu is a residential neighborhood and transport hub in Hong Kong known for its public housing estates, shopping centre, and MTR station.
- 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_6a0170df4d1c81909dd05abfd1cfc2ac |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:33 a.m.