Triple
T18330562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mistresses |
E439126
|
entity |
| Predicate | leadActor |
P1507
|
FINISHED |
| Object | Yunjin Kim |
E1318400
|
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: Yunjin Kim | Statement: [Mistresses, leadActor, Yunjin Kim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yunjin Kim Context triple: [Mistresses, leadActor, Yunjin Kim]
-
A.
Kinam Kim
Kinam Kim is a prominent South Korean semiconductor executive and technologist recognized for his leadership and contributions to the global chip industry.
-
B.
So-hee Kim
So-hee Kim is a television producer best known for her executive production work on the historical sci-fi drama series "Project Blue Book."
-
C.
Da-yeon Jung
Da-yeon Jung is a Korean individual notable enough to be recognized as a prominent bearer of the surname Jung.
-
D.
Ko-Yeon Jeon
Ko-Yeon Jeon is the traditional and highly anticipated annual sports rivalry event between Yonsei University and Korea University in South Korea.
-
E.
Karen Kim
chosen
Karen Kim is a central character in the TV drama "Mistresses," known for her complex personal life and morally ambiguous romantic entanglements.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ec900808190bc4468270e0957c1 |
completed | April 19, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03cc1db9e88190915f71afca4ae3e7 |
completed | May 13, 2026, 12:55 a.m. |
Created at: April 10, 2026, 10:36 a.m.