Triple
T10353546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myung-whun Chung |
E243940
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Kyung-wha Chung |
E711089
|
NE FINISHED |
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: Kyung-wha Chung | Statement: [Myung-whun Chung, sibling, Kyung-wha Chung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kyung-wha Chung Context triple: [Myung-whun Chung, sibling, Kyung-wha Chung]
-
A.
Kyung Wha Chung
chosen
Kyung Wha Chung is a renowned South Korean violinist celebrated for her virtuosic technique and international solo career.
-
B.
Wookyung Jung
Wookyung Jung is a film producer best known for working on the animated feature "The Nut Job."
-
C.
Kinam Kim
Kinam Kim is a prominent South Korean semiconductor executive and technologist recognized for his leadership and contributions to the global chip industry.
-
D.
Nakyung Park
Nakyung Park is a South Korean painter and artist best known publicly as the wife of American actor Wesley Snipes.
-
E.
Soo-Yung Han
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e952c878819084e5d7a593a3f9e9 |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7509c50d48190a567d9613a062efc |
completed | April 9, 2026, 7:09 a.m. |
Created at: April 6, 2026, 11:58 a.m.