Triple
T21869482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Train to Busan |
E539964
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Choi Gwi-hwa
Choi Gwi-hwa is a South Korean actor known for his supporting roles in popular films and television dramas, including the hit zombie thriller "Train to Busan."
|
E1556215
|
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: Choi Gwi-hwa | Statement: [Train to Busan, portrayedBy, Choi Gwi-hwa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Choi Gwi-hwa Context triple: [Train to Busan, portrayedBy, Choi Gwi-hwa]
-
A.
Jeon Mi-do
Jeon Mi-do is a South Korean actress and musical theatre performer best known for her breakout television role in the acclaimed drama series "Hospital Playlist."
-
B.
Son Byeong-hui
Son Byeong-hui was a prominent Korean religious and independence leader who modernized the Donghak movement into Cheondogyo and played a key role in the March 1st Movement against Japanese colonial rule.
-
C.
Suh Jin-suk
Suh Jin-suk is a notable individual who prominently bears the Korean surname Suh.
-
D.
Yu Jae-sun
Yu Jae-sun is a film producer best known for producing the South Korean movie "Silenced."
-
E.
Choi Soo-in
Choi Soo-in is a South Korean child actress known for her acclaimed lead role in the coming-of-age film "The World of Us."
- 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: Choi Gwi-hwa Triple: [Train to Busan, portrayedBy, Choi Gwi-hwa]
Generated description
Choi Gwi-hwa is a South Korean actor known for his supporting roles in popular films and television dramas, including the hit zombie thriller "Train to Busan."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Choi Gwi-hwa Target entity description: Choi Gwi-hwa is a South Korean actor known for his supporting roles in popular films and television dramas, including the hit zombie thriller "Train to Busan."
-
A.
Jeon Mi-do
Jeon Mi-do is a South Korean actress and musical theatre performer best known for her breakout television role in the acclaimed drama series "Hospital Playlist."
-
B.
Son Byeong-hui
Son Byeong-hui was a prominent Korean religious and independence leader who modernized the Donghak movement into Cheondogyo and played a key role in the March 1st Movement against Japanese colonial rule.
-
C.
Suh Jin-suk
Suh Jin-suk is a notable individual who prominently bears the Korean surname Suh.
-
D.
Yu Jae-sun
Yu Jae-sun is a film producer best known for producing the South Korean movie "Silenced."
-
E.
Choi Soo-in
Choi Soo-in is a South Korean child actress known for her acclaimed lead role in the coming-of-age film "The World of Us."
- 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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f334362c819094af465ee57b47e6 |
completed | April 28, 2026, 5:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ba791d9ec81908a518673ed3dd04b |
completed | May 18, 2026, 11:58 p.m. |
| NEDg | Description generation | batch_6a0ba81bade88190bc0f4225600509a2 |
completed | May 19, 2026, midnight |
| NED2 | Entity disambiguation (via description) | batch_6a0ba8c3d6c88190944df9358dd58c4e |
completed | May 19, 2026, 12:03 a.m. |
Created at: April 16, 2026, 6:57 p.m.