Triple
T22003966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunt |
E543402
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jeon Hye-jin |
—
|
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: Jeon Hye-jin | Statement: [Hunt, starring, Jeon Hye-jin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeon Hye-jin Context triple: [Hunt, starring, Jeon Hye-jin]
-
A.
Jeon Hye-jin
chosen
Jeon Hye-jin is a South Korean actress known for her work in film and television.
-
B.
Seol Hye-in
Seol Hye-in is a South Korean actress known for her role in the coming-of-age film "The World of Us."
-
C.
Jang Hye-jin
Jang Hye-jin is a South Korean actress best known internationally for her role as the resourceful housekeeper in the Academy Award–winning film "Parasite."
-
D.
Hong Yoon-jeong
Hong Yoon-jeong is a South Korean screenwriter best known for her work on the hit fantasy-comedy film "Miss Granny."
-
E.
Eun Soo-kyung
Eun Soo-kyung is a South Korean film editor known for her work on notable contemporary Korean cinema, including the 2010 thriller "The Housemaid."
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1276cab5c8190ac1236fde7e0394a |
completed | April 28, 2026, 9:32 p.m. |
Created at: April 16, 2026, 8:20 p.m.