Triple
T17025686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wheels on Meals |
E413057
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Barry Wong |
—
|
NE NERFINISHED |
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: Barry Wong | Statement: [Wheels on Meals, writer, Barry Wong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barry Wong Context triple: [Wheels on Meals, writer, Barry Wong]
-
A.
Barry Wong
chosen
Barry Wong was a prolific Hong Kong screenwriter and occasional actor known for his influential work on action and comedy films during the 1980s and early 1990s.
-
B.
Victor Wong
Victor Wong was an American character actor known for his distinctive presence in films such as "The Last Emperor," "Big Trouble in Little China," and "Tremors."
-
C.
Stephen Wong
Stephen Wong is a technology entrepreneur best known as a founder of the software company Embarcadero Technologies.
-
D.
Sean Wong
Sean Wong is an American writer and editor known for his contributions to Asian American literature and for co-founding the Before Columbus Foundation, which promotes multicultural literature.
-
E.
Kenny Wong
Kenny Wong is an actor known for appearing in the action film "Expend4bles," part of the Expendables franchise.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e3d5d46a5081908bc5681621dd8534 |
completed | April 18, 2026, 7:04 p.m. |
Created at: April 10, 2026, 5:33 a.m.