Triple
T21869478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Train to Busan |
E539964
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Jung Yu-mi |
—
|
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: Jung Yu-mi | Statement: [Train to Busan, portrayedBy, Jung Yu-mi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jung Yu-mi Context triple: [Train to Busan, portrayedBy, Jung Yu-mi]
-
A.
Jung Yu-mi
chosen
Jung Yu-mi is a South Korean actress known for her versatile performances in acclaimed films and television dramas such as "Train to Busan," "The Crucible," and "Discovery of Love."
-
B.
Lee Yoo-mi
Lee Yoo-mi is a South Korean actress best known internationally for her breakout role in the Netflix series "Squid Game."
-
C.
Jeong Ji-hyun
Jeong Ji-hyun is a Korean individual whose name is romanized from the Korean name Ji-hyun Jung.
-
D.
Koh Hyun-jung
Koh Hyun-jung is a prominent South Korean actress and former Miss Korea runner-up, known for her acclaimed roles in television dramas and films.
-
E.
Suh Ji-hyun
Suh Ji-hyun is a South Korean individual notable for bearing the Korean surname Suh.
- 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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f334362c819094af465ee57b47e6 |
completed | April 28, 2026, 5:49 p.m. |
Created at: April 16, 2026, 6:57 p.m.