Triple
T6026876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wi Ha-joon |
E134202
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 위하준 |
E134202
|
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: 위하준 | Statement: [Wi Ha-joon, nativeName, 위하준]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 위하준 Context triple: [Wi Ha-joon, nativeName, 위하준]
-
A.
Lee Tae-hun
Lee Tae-hun is a South Korean film producer known for his work on the international release of the science fiction thriller "Snowpiercer."
-
B.
Wi Ha-joon
chosen
Wi Ha-joon is a South Korean actor and model best known internationally for his breakout role in the hit Netflix survival drama series "Squid Game."
-
C.
Hwang In-ho
Hwang In-ho is a mysterious character in the South Korean series "Squid Game," known as the Front Man and the missing brother of police officer Hwang Jun-ho.
-
D.
Oh Se-hoon
Oh Se-hoon is a South Korean politician best known for serving multiple terms as the mayor of Seoul.
-
E.
Choi "HuHi" Jae-hyun
Choi "HuHi" Jae-hyun is a professional South Korean League of Legends mid laner known for his competitive play in the North American LCS.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0560cdc308190b25ca8ecb42c4e4f |
completed | March 22, 2026, 8:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c113799d648190a08516a33a5f92b7 |
completed | March 23, 2026, 10:18 a.m. |
Created at: March 22, 2026, 4:07 p.m.