Triple
T5859905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jung Ho-yeon |
E130249
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | 정호연 |
E130249
|
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: 정호연 | Statement: [Jung Ho-yeon, nativeName, 정호연]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 정호연 Context triple: [Jung Ho-yeon, nativeName, 정호연]
-
A.
Jung Ho-yeon
chosen
Jung Ho-yeon is a South Korean model-turned-actress who gained international fame for her breakout role in the Netflix survival drama series "Squid Game."
-
B.
김소연
김소연은 한국 출신으로 독일 전 총리 게르하르트 슈뢰더의 아내로 알려진 인물이다.
-
C.
Cho Yo-han
Cho Yo-han is the Korean birth name of John Cho, a Korean American actor best known for his roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
-
D.
Heo Jeong
Heo Jeong was a South Korean politician who served as prime minister and played a significant role in the country’s early post-war democratic politics.
-
E.
Kim Joo-ryoung
Kim Joo-ryoung is a South Korean actress best known internationally for her role in the hit Netflix survival drama series "Squid Game."
- 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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0358790b88190a5e3c6473172dc53 |
completed | March 22, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e36fa8ac8190add9a5eb3ada4d0f |
completed | March 23, 2026, 6:53 a.m. |
Created at: March 22, 2026, 3:56 p.m.