Triple
T14487567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dragon: The Bruce Lee Story |
E359274
|
entity |
| Predicate | portrays |
P264
|
FINISHED |
| Object | Bruce Lee |
E273351
|
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: Bruce Lee | Statement: [Dragon: The Bruce Lee Story, portrays, Bruce Lee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bruce Lee Context triple: [Dragon: The Bruce Lee Story, portrays, Bruce Lee]
-
A.
Bruce Lee
chosen
Bruce Lee was a legendary Hong Kong-American martial artist, actor, and filmmaker who revolutionized martial arts cinema and popularized kung fu worldwide.
-
B.
Brandon Lee
Brandon Lee was an American actor and martial artist, best known for his lead role in the film "The Crow" and for being the son of Bruce Lee.
-
C.
Jackie Chan
Jackie Chan is a Hong Kong martial artist, actor, stuntman, and filmmaker renowned worldwide for his acrobatic fighting style, innovative stunts, and blend of action and comedy in films.
-
D.
Keye Luke
Keye Luke was a Chinese-American actor and artist best known for his roles in the Charlie Chan films, the original "Kung Fu" TV series, and as Master Po in "Kung Fu."
-
E.
Jimmy Lei Ba
Jimmy Lei Ba is a machine learning researcher known for influential contributions to deep learning optimization and normalization techniques, including the development of Layer Normalization.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924ee0f08190baf68318b41fa64d |
completed | April 14, 2026, 7:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a3e32fc8190822aeb633b60af6b |
completed | May 8, 2026, 5:53 a.m. |
Created at: April 10, 2026, 1:20 a.m.