Triple
T19410922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 정재일 |
E485582
|
entity |
| Predicate | 알려진_분야 |
P39276
|
FINISHED |
| Object | 영화·드라마 음악 |
—
|
LITERAL FINISHED |
How this triple was built (2 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: 영화·드라마 음악 | Statement: [정재일, 알려진_분야, 영화·드라마 음악]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 알려진_분야 Context triple: [정재일, 알려진_분야, 영화·드라마 음악]
-
A.
practicedInField
Indicates that an entity has engaged in practical work, training, or professional activity within a specified field or domain.
-
B.
developedInField
Indicates that an entity (such as a method, theory, or technology) was created, formulated, or advanced within a particular academic or professional field.
-
C.
theorizedInField
Indicates that a theory, idea, or hypothesis was formulated or developed within a particular academic or scientific field.
-
D.
knowledgeScope
Indicates the extent or range of information, topics, or understanding that an entity possesses or is concerned with.
-
E.
notableField
chosen
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
- F. None of above.
Provenance (3 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. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.