Triple
T19411199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The World of Us |
E485591
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Yoon Ga-eun |
—
|
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: Yoon Ga-eun | Statement: [The World of Us, screenwriter, Yoon Ga-eun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yoon Ga-eun Context triple: [The World of Us, screenwriter, Yoon Ga-eun]
-
A.
Yoon Ga-eun
chosen
Yoon Ga-eun is a South Korean film director and screenwriter known for her sensitive, realistic portrayals of children and adolescence.
-
B.
Shim Eun-kyung
Shim Eun-kyung is a South Korean actress known for her versatile performances in film and television, particularly in comedic and dramatic roles.
-
C.
Won Jin-ah
Won Jin-ah is a South Korean actress known for her roles in television dramas and films, including the dark fantasy series "Hellbound."
-
D.
Jo Yun-ok
Jo Yun-ok is the wife of renowned Hong Kong martial artist, actor, and film director Sammo Hung.
-
E.
Lee Hae-jin
Lee Hae-jin is a South Korean entrepreneur and technologist best known as the founder and longtime leader of internet giant Naver Corporation.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af681288190ba2ec52d5adb6a22 |
completed | April 20, 2026, 1:32 p.m. |
Created at: April 10, 2026, 1:37 p.m.