Triple
T6061201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuna Kim |
E135035
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object |
Kim Yuna
Kim Yuna is a South Korean figure skater widely regarded as one of the greatest in the sport’s history, known for her Olympic gold medal and record-breaking performances.
|
E566383
|
NE FINISHED |
How this triple was built (4 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 Yuna | Statement: [Yuna Kim, name, Kim Yuna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Yuna Context triple: [Yuna Kim, name, Kim Yuna]
-
A.
Wi Hyun-yi
Wi Hyun-yi is the birth name of South Korean actor and model Wi Ha-joon, known internationally for his roles in popular Korean dramas and films.
-
B.
Son Mi-na
Son Mi-na is a South Korean athlete best known for delivering the Olympic Oath on behalf of all competitors at the 1988 Seoul Summer Games.
-
C.
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."
-
D.
Da-yeon Jung
Da-yeon Jung is a Korean individual notable enough to be recognized as a prominent bearer of the surname Jung.
-
E.
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."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kim Yuna Triple: [Yuna Kim, name, Kim Yuna]
Generated description
Kim Yuna is a South Korean figure skater widely regarded as one of the greatest in the sport’s history, known for her Olympic gold medal and record-breaking performances.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kim Yuna Target entity description: Kim Yuna is a South Korean figure skater widely regarded as one of the greatest in the sport’s history, known for her Olympic gold medal and record-breaking performances.
-
A.
Wi Hyun-yi
Wi Hyun-yi is the birth name of South Korean actor and model Wi Ha-joon, known internationally for his roles in popular Korean dramas and films.
-
B.
Son Mi-na
Son Mi-na is a South Korean athlete best known for delivering the Olympic Oath on behalf of all competitors at the 1988 Seoul Summer Games.
-
C.
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."
-
D.
Da-yeon Jung
Da-yeon Jung is a Korean individual notable enough to be recognized as a prominent bearer of the surname Jung.
-
E.
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."
- F. None of above. chosen
Provenance (5 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_69c00878d06881909ee78e88913bf890 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0571fcecc8190a68e0d0668bbbfa7 |
completed | March 22, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d197dd08190bcc6904c7c2e41aa |
completed | March 23, 2026, 10:59 a.m. |
| NEDg | Description generation | batch_69c11e4454948190a8f4643cb55e673a |
completed | March 23, 2026, 11:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c11ec554688190bfe184608944a15e |
completed | March 23, 2026, 11:06 a.m. |
Created at: March 22, 2026, 4:10 p.m.