Triple
T3460420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | We Can Be Heroes |
E73009
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Sung Kang |
E268557
|
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: Sung Kang | Statement: [We Can Be Heroes, stars, Sung Kang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sung Kang Context triple: [We Can Be Heroes, stars, Sung Kang]
-
A.
Sung Kang
chosen
Sung Kang is an American actor best known for his role as Han Lue in the Fast & Furious film franchise.
-
B.
John Cho
John Cho is a Korean American actor best known for his roles in the "Harold & Kumar" comedy series and as Hikaru Sulu in the rebooted "Star Trek" film franchise.
-
C.
Haan Lee
Haan Lee is one of the children of acclaimed Taiwanese-American film director Ang Lee.
-
D.
Peter Sohn
Peter Sohn is an American animator, voice actor, and film director at Pixar known for his work on projects like "Ratatouille," "The Good Dinosaur," and "Elemental."
-
E.
Simu Liu
Simu Liu is a Chinese Canadian actor best known for starring as the Marvel superhero Shang-Chi and appearing in the sitcom "Kim's Convenience" and the film "Barbie."
- 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_69ad85b224d481908ff8be51338d24ff |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae5ff848190880fa416a123bc4a |
completed | March 8, 2026, 6:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b361093d288190a023e8485265a989 |
completed | March 13, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:17 p.m.