Triple
T4977386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ojingeo Geim |
E111800
|
entity |
| Predicate | leadActor |
P1507
|
FINISHED |
| Object | Wi Ha-joon |
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: Wi Ha-joon | Statement: [Ojingeo Geim, leadActor, Wi Ha-joon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wi Ha-joon Context triple: [Ojingeo Geim, leadActor, Wi Ha-joon]
-
A.
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."
-
B.
Ban Woo-hyun
Ban Woo-hyun is one of the children of former UN Secretary-General Ban Ki-moon and his wife Yoo Soon-taek.
-
C.
Oh Se-hoon
Oh Se-hoon is a South Korean politician best known for serving multiple terms as the mayor of Seoul.
-
D.
Koo In-hwoi
Koo In-hwoi was a South Korean entrepreneur who built one of the country’s leading chaebols, the LG Group, helping pioneer its modern electronics and chemical industries.
-
E.
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."
- 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7231448c8190a5d0a5135a9cfdf1 |
completed | March 20, 2026, 4:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec34a07c0819089953ebcbe9cc3ff |
completed | March 21, 2026, 4:11 p.m. |
Created at: March 20, 2026, 1:33 p.m.