Triple
T22161208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yaksha: Ruthless Operations |
E547672
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Na Hyeon |
—
|
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: Na Hyeon | Statement: [Yaksha: Ruthless Operations, writer, Na Hyeon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Na Hyeon Context triple: [Yaksha: Ruthless Operations, writer, Na Hyeon]
-
A.
Na Hyeon
chosen
Na Hyeon is a South Korean film director best known for helming the action thriller "Yaksha: Ruthless Operations."
-
B.
Nam Na-yeong
Nam Na-yeong is a South Korean film editor known for her work on numerous popular and critically acclaimed Korean films.
-
C.
Kim Seung-yeon
Kim Seung-yeon is a South Korean businessman best known as the longtime chairman and leader of the Hanwha Group conglomerate.
-
D.
Son Mi-na
Son Mi-na is a South Korean athlete best known for delivering the Olympic Oath on behalf of all competitors at the 1988 Seoul Summer Games.
-
E.
Bae Young-soo
Bae Young-soo is a South Korean former professional baseball pitcher best known for his successful career in the KBO League, particularly with the Samsung Lions.
- 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_69e11e3c4c5c81908d336165816b12e0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a2d8064819094d27ef9f15c6a1f |
completed | April 28, 2026, 9:44 p.m. |
Created at: April 16, 2026, 8:34 p.m.