Triple
T21211146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Consul Solon Han |
E522721
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object | Soo-Yung Han |
—
|
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: Soo-Yung Han | Statement: [Consul Solon Han, associatedWithCharacter, Soo-Yung Han]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soo-Yung Han Context triple: [Consul Solon Han, associatedWithCharacter, Soo-Yung Han]
-
A.
Soo-Yung Han
chosen
Soo-Yung Han is the young daughter of a Chinese consul whose kidnapping repeatedly drives the central plot and emotional stakes of the Rush Hour film series.
-
B.
Sung-Hi Lee
Sung-Hi Lee is a Korean-born American model and actress known for her work in magazines, films, and television.
-
C.
Wookyung Jung
Wookyung Jung is a film producer best known for working on the animated feature "The Nut Job."
-
D.
In-Kyung Kim
In-Kyung Kim is a South Korean professional golfer known for her multiple LPGA Tour victories and strong performances in international tournaments.
-
E.
Ji-Yoon Kim
Ji-Yoon Kim is the beleaguered yet determined new chair of a struggling university English department in the Netflix dramedy "The Chair," juggling academic politics, cultural change, and single motherhood.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7346eb20c8190aeb3c0cc0a24aaf9 |
completed | April 21, 2026, 8:25 a.m. |
Created at: April 16, 2026, 3:37 p.m.