Triple
T9352158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Savio Kwan |
E225042
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Savio Kwan |
E225042
|
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: Savio Kwan | Statement: [Savio Kwan, name, Savio Kwan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Savio Kwan Context triple: [Savio Kwan, name, Savio Kwan]
-
A.
Savio Kwan
chosen
Savio Kwan is a business executive best known for his leadership roles at Alibaba Group, where he helped guide the company’s early growth and international expansion.
-
B.
Chan Wing-yan
Chan Wing-yan is the undercover police officer protagonist in the Hong Kong crime thriller series "Infernal Affairs," known for infiltrating the triads at great personal cost.
-
C.
Chan Kwong-wing
Chan Kwong-wing is a Hong Kong film composer best known for his scores for acclaimed movies such as the Infernal Affairs trilogy.
-
D.
Ronald Cheng
Ronald Cheng is a Hong Kong actor and Cantopop singer known for his comedic film roles and successful music career.
-
E.
Ryan Chan
Ryan Chan is a film editor known for his work on the 2020 adaptation of "The Witches."
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f93a9848190ad2ae24f2aa607d2 |
completed | April 1, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e44f0a7881908b53a97715f4c6da |
completed | April 4, 2026, 10:13 a.m. |
Created at: March 30, 2026, 7:41 p.m.