Triple
T21869519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burning |
E539965
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Kim Hyun |
—
|
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: Kim Hyun | Statement: [Burning, editedBy, Kim Hyun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Hyun Context triple: [Burning, editedBy, Kim Hyun]
-
A.
Kim Hyun
chosen
Kim Hyun is a South Korean designer best known for creating Hodori, the official tiger mascot of the 1988 Seoul Olympic Games.
-
B.
Hwang Jo-yoon
Hwang Jo-yoon is a South Korean screenwriter best known for co-writing the acclaimed neo-noir revenge film "Oldboy."
-
C.
Ahn Soo-hyun
Ahn Soo-hyun is a South Korean film producer best known for producing the acclaimed historical action film "Assassination."
-
D.
Jin Ha
Jin Ha is a Korean-American actor known for his roles in television series such as "Devs" and "Pachinko," as well as his work on stage in productions like "Hamilton."
-
E.
Ahn Seo-hyun
Ahn Seo-hyun is a South Korean actress best known internationally for her lead role in Bong Joon-ho’s film "Okja."
- 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.