Triple
T5142009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Cho |
E115973
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | John Cho |
E115973
|
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: John Cho | Statement: [John Cho, name, John Cho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Cho Context triple: [John Cho, name, John Cho]
-
A.
John Cho
chosen
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.
-
B.
Byung-hun Lee
Byung-hun Lee is a prominent South Korean actor known internationally for his roles in both Korean cinema and Hollywood films, including major action and thriller productions.
-
C.
Jason Scott Lee
Jason Scott Lee is an American actor and martial artist best known for his lead role in the biographical film "Dragon: The Bruce Lee Story" and various voice and live-action performances in film and television.
-
D.
Ken Jeong
Ken Jeong is an American comedian, actor, and licensed physician best known for his roles in "The Hangover" film series and the TV show "Community."
-
E.
Sung Kang
Sung Kang is an American actor best known for his role as Han Lue in the Fast & Furious film franchise.
- 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd787ff1c081909a6954aa76e12cbf |
completed | March 20, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69becfe7370c8190a47070487b461114 |
completed | March 21, 2026, 5:05 p.m. |
Created at: March 20, 2026, 1:43 p.m.