Triple
T21273341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hwang In-ho |
E524323
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Lee Byung-hun |
—
|
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: Lee Byung-hun | Statement: [Hwang In-ho, portrayedBy, Lee Byung-hun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lee Byung-hun Context triple: [Hwang In-ho, portrayedBy, Lee Byung-hun]
-
A.
Lee Jung-jae
Lee Jung-jae is a South Korean actor and former model renowned for his versatile film and television roles, gaining worldwide fame for his performance in the Netflix series "Squid Game."
-
B.
Bong Hyo-min
Bong Hyo-min is the child of acclaimed South Korean film director and screenwriter Bong Joon-ho.
-
C.
Jang Hoon
Jang Hoon is a South Korean film director known for commercially successful and critically acclaimed movies that blend genre entertainment with social and political themes.
-
D.
Gong Yoo
Gong Yoo is a South Korean actor renowned for his versatile performances in film and television, including major roles in works like "Train to Busan" and the drama "Goblin."
-
E.
Byung-hun Lee
chosen
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.
- 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_69e0b516293c819089458ea2ec85f85e |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73655717c819092f71ed1920f52b5 |
completed | April 21, 2026, 8:33 a.m. |
Created at: April 16, 2026, 4:01 p.m.