Triple
T19410721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Granny |
E485578
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Nam Na-yeong
Nam Na-yeong is a South Korean film editor known for her work on numerous popular and critically acclaimed Korean films.
|
E1384386
|
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: Nam Na-yeong | Statement: [Miss Granny, editedBy, Nam Na-yeong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nam Na-yeong Context triple: [Miss Granny, editedBy, Nam Na-yeong]
-
A.
Cha Jeong-in
Cha Jeong-in is a South Korean academic who serves as the president of Pusan National University.
-
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.
Heo Jeong
Heo Jeong was a South Korean politician who served as prime minister and played a significant role in the country’s early post-war democratic politics.
-
D.
Jung Sun-young
Jung Sun-young is the wife of acclaimed South Korean film director Bong Joon-ho.
-
E.
Jeong Eun-ji
Jeong Eun-ji is a South Korean singer and actress best known as the main vocalist of the girl group Apink and for her roles in popular television dramas.
- 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: Nam Na-yeong Triple: [Miss Granny, editedBy, Nam Na-yeong]
Generated description
Nam Na-yeong is a South Korean film editor known for her work on numerous popular and critically acclaimed Korean films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nam Na-yeong Target entity description: Nam Na-yeong is a South Korean film editor known for her work on numerous popular and critically acclaimed Korean films.
-
A.
Cha Jeong-in
Cha Jeong-in is a South Korean academic who serves as the president of Pusan National University.
-
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.
Heo Jeong
Heo Jeong was a South Korean politician who served as prime minister and played a significant role in the country’s early post-war democratic politics.
-
D.
Jung Sun-young
Jung Sun-young is the wife of acclaimed South Korean film director Bong Joon-ho.
-
E.
Jeong Eun-ji
Jeong Eun-ji is a South Korean singer and actress best known as the main vocalist of the girl group Apink and for her roles in popular television dramas.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e62af4cc0c81909056b5e2ee574ab1 |
completed | April 20, 2026, 1:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a075ef8fd0c819090ddc1e1dba8477c |
completed | May 15, 2026, 5:59 p.m. |
| NEDg | Description generation | batch_6a075fbe27a081909c6869abfdfb6079 |
completed | May 15, 2026, 6:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07608dfcb481908833ecb65c10b96b |
completed | May 15, 2026, 6:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.