Triple
T5859906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jung Ho-yeon |
E130249
|
entity |
| Predicate | romanization |
P2508
|
FINISHED |
| Object | Jeong Ho-yeon |
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: Jeong Ho-yeon | Statement: [Jung Ho-yeon, romanization, Jeong Ho-yeon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeong Ho-yeon Context triple: [Jung Ho-yeon, romanization, Jeong Ho-yeon]
-
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.
Jung Sun-young
Jung Sun-young is the wife of acclaimed South Korean film director Bong Joon-ho.
-
C.
Cha Jeong-in
Cha Jeong-in is a South Korean academic who serves as the president of Pusan National University.
-
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.
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.
- 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_69c124f45d8c8190a757c82abd85c514 |
completed | March 23, 2026, 11:33 a.m. |
Created at: March 22, 2026, 3:56 p.m.