Triple
T5648599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Han Mi-nyeo |
E124444
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Kim Joo-ryoung |
E489490
|
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: Kim Joo-ryoung | Statement: [Han Mi-nyeo, portrayedBy, Kim Joo-ryoung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Joo-ryoung Context triple: [Han Mi-nyeo, portrayedBy, Kim Joo-ryoung]
-
A.
Kim Joo-ryoung
chosen
Kim Joo-ryoung is a South Korean actress best known internationally for her role in the hit Netflix survival drama series "Squid Game."
-
B.
Cho Yeo-jeong
Cho Yeo-jeong is a South Korean actress best known internationally for her role as the wealthy Park family mother in the Academy Award–winning film "Parasite."
-
C.
Jo Yun-ok
Jo Yun-ok is the wife of renowned Hong Kong martial artist, actor, and film director Sammo Hung.
-
D.
Jung Ho-yeon
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."
-
E.
Jang Hye-jin
Jang Hye-jin is a South Korean actress best known internationally for her role as the resourceful housekeeper in the Academy Award–winning film "Parasite."
- 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_69c00825df388190a58742fa9b1aa33d |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c022d1534c8190ac4828e44300fb91 |
completed | March 22, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d8cea4481908fccb8ed102b18a1 |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 3:42 p.m.