Triple
T19410732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Granny |
E485578
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object |
Na Moon-hee
Na Moon-hee is a veteran South Korean actress renowned for her versatile performances in film and television over several decades.
|
E1386058
|
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: Na Moon-hee | Statement: [Miss Granny, stars, Na Moon-hee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Na Moon-hee Context triple: [Miss Granny, stars, Na Moon-hee]
-
A.
Han Mi-nyeo
Han Mi-nyeo is a loud, manipulative, and opportunistic contestant in the South Korean survival drama series "Squid Game," known for her volatile alliances and dramatic personality.
-
B.
Lee Maeng-hee
Lee Maeng-hee was a South Korean businessman best known as the eldest son of Samsung founder Lee Byung-chul and a former executive within the Samsung Group.
-
C.
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.
-
D.
Oh Kyo-moon
Oh Kyo-moon is a South Korean archer who won multiple Olympic medals in the 1990s and early 2000s.
-
E.
Ju-Hee
Ju-Hee is the child of Ji-Yoon Kim, likely a member of a Korean family.
- 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: Na Moon-hee Triple: [Miss Granny, stars, Na Moon-hee]
Generated description
Na Moon-hee is a veteran South Korean actress renowned for her versatile performances in film and television over several decades.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Na Moon-hee Target entity description: Na Moon-hee is a veteran South Korean actress renowned for her versatile performances in film and television over several decades.
-
A.
Han Mi-nyeo
Han Mi-nyeo is a loud, manipulative, and opportunistic contestant in the South Korean survival drama series "Squid Game," known for her volatile alliances and dramatic personality.
-
B.
Lee Maeng-hee
Lee Maeng-hee was a South Korean businessman best known as the eldest son of Samsung founder Lee Byung-chul and a former executive within the Samsung Group.
-
C.
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.
-
D.
Oh Kyo-moon
Oh Kyo-moon is a South Korean archer who won multiple Olympic medals in the 1990s and early 2000s.
-
E.
Ju-Hee
Ju-Hee is the child of Ji-Yoon Kim, likely a member of a Korean family.
- 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_6a07719ca57c8190acf3befafc0ab287 |
completed | May 15, 2026, 7:18 p.m. |
| NEDg | Description generation | batch_6a0773a7b6c48190bc7749fb03153745 |
completed | May 15, 2026, 7:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0774088414819098b770c2af602507 |
completed | May 15, 2026, 7:29 p.m. |
Created at: April 10, 2026, 1:37 p.m.