Triple
T19626136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suh Yun-bok |
E471139
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Suh Yun-bok |
—
|
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: Suh Yun-bok | Statement: [Suh Yun-bok, name, Suh Yun-bok]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suh Yun-bok Context triple: [Suh Yun-bok, name, Suh Yun-bok]
-
A.
Suh Yun-bok
chosen
Suh Yun-bok was a South Korean long-distance runner best known for winning the 1947 Boston Marathon and later serving as a symbolic sports figure in Korea.
-
B.
Jeong Jin-soo
Jeong Jin-soo is the enigmatic and charismatic cult leader at the center of the South Korean dark fantasy series "Hellbound," whose prophecies about divine judgment drive the show's apocalyptic events.
-
C.
Yoon Deok-soo
Yoon Deok-soo is the resilient everyman protagonist of the South Korean film "Ode to My Father," whose life story reflects the struggles and sacrifices of Korea’s post-war generation.
-
D.
Suh Yong-jun
Suh Yong-jun is a Korean individual notable enough to be recognized as a prominent bearer of the surname Suh.
-
E.
Moon Sung-keun
Moon Sung-keun is a South Korean actor and former politician known for his roles in socially conscious films and television dramas.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640e9ff208190afb33c910ed2147b |
completed | April 20, 2026, 3:06 p.m. |
Created at: April 10, 2026, 1:44 p.m.