Triple
T19562560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Joo-ryoung |
E489490
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Kim Joo-ryoung |
—
|
NE NERFINISHED |
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: [Kim Joo-ryoung, name, Kim Joo-ryoung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Joo-ryoung Context triple: [Kim Joo-ryoung, name, 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.
Kim So-yeon
Kim So-yeon, better known as Soyeon Schröder-Kim, is a South Korean-born interpreter who is publicly known as the wife of former German Chancellor Gerhard Schröder.
-
C.
Lee Joo-young
Lee Joo-young is a South Korean actress known for her roles in independent films and television dramas, often portraying complex, unconventional characters.
-
D.
Jung Yu-mi
Jung Yu-mi is a South Korean actress known for her versatile performances in acclaimed films and television dramas such as "Train to Busan," "The Crucible," and "Discovery of Love."
-
E.
Jung Jin-young
Jung Jin-young is a South Korean actor known for his versatile performances in film and television, often portraying complex and emotionally resonant characters.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f74fdb08190852461b5d5c954ac |
completed | April 20, 2026, 3 p.m. |
Created at: April 10, 2026, 1:42 p.m.