Triple
T21869474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Train to Busan |
E539964
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Yon-suk
Yon-suk is the selfish and antagonistic businessman in the South Korean zombie film "Train to Busan," known for endangering others to save himself.
|
E1514319
|
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: Yon-suk | Statement: [Train to Busan, mainCharacter, Yon-suk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yon-suk Context triple: [Train to Busan, mainCharacter, Yon-suk]
-
A.
Yong-taek
Yong-taek is a Korean masculine given name commonly used in South Korea.
-
B.
Yong-gi
Yong-gi is a Korean given name commonly used for males.
-
C.
Yong-il
Yong-il is a Korean masculine given name that can be shared by various individuals, including notable figures such as politicians and public officials.
-
D.
Seonghwan
Seonghwan is a locality in South Korea historically noted as the site of the Battle of Seonghwan during the First Sino-Japanese War.
-
E.
Dong-soo
Dong-soo is a central character in the South Korean film "Broker," portrayed as a morally conflicted man involved in an illegal baby adoption scheme.
- 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: Yon-suk Triple: [Train to Busan, mainCharacter, Yon-suk]
Generated description
Yon-suk is the selfish and antagonistic businessman in the South Korean zombie film "Train to Busan," known for endangering others to save himself.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yon-suk Target entity description: Yon-suk is the selfish and antagonistic businessman in the South Korean zombie film "Train to Busan," known for endangering others to save himself.
-
A.
Yong-taek
Yong-taek is a Korean masculine given name commonly used in South Korea.
-
B.
Yong-gi
Yong-gi is a Korean given name commonly used for males.
-
C.
Yong-il
Yong-il is a Korean masculine given name that can be shared by various individuals, including notable figures such as politicians and public officials.
-
D.
Seonghwan
Seonghwan is a locality in South Korea historically noted as the site of the Battle of Seonghwan during the First Sino-Japanese War.
-
E.
Dong-soo
Dong-soo is a central character in the South Korean film "Broker," portrayed as a morally conflicted man involved in an illegal baby adoption scheme.
- 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_6a0a7361a24081908b1334e2ad9923f9 |
completed | May 18, 2026, 2:03 a.m. |
| NEDg | Description generation | batch_6a0a780f0c008190bd56b7af0bebbc85 |
completed | May 18, 2026, 2:23 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a78c2a94c8190841463b0a52ba16e |
completed | May 18, 2026, 2:26 a.m. |
Created at: April 16, 2026, 6:57 p.m.