Triple
T16850406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unforgettable (2017 film) |
E409658
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Toby Chu |
E796029
|
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: Toby Chu | Statement: [Unforgettable (2017 film), musicBy, Toby Chu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toby Chu Context triple: [Unforgettable (2017 film), musicBy, Toby Chu]
-
A.
Toby Chu
chosen
Toby Chu is a film and television composer known for scoring projects such as the sci-fi series "Colony" and various animated and live-action works.
-
B.
Felix Chong
Felix Chong is a Hong Kong filmmaker best known as the co-writer and co-creator of the acclaimed crime thriller series "Infernal Affairs," which inspired Martin Scorsese’s "The Departed."
-
C.
Robbi Chong
Robbi Chong is a Canadian actress and former model known for her film and television roles in the 1980s and 1990s.
-
D.
Topher Ngo
Topher Ngo is a voice actor and singer best known for his role in Pixar's animated film "Turning Red."
-
E.
Christopher Chung
Christopher Chung is an actor known for his role in the British spy drama series "Slow Horses."
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b378dda48190ab81d75f2cfe3ab3 |
completed | April 18, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb1f02648190937c692af83843dc |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 5:24 a.m.