Triple
T22161108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 박해수 |
E547669
|
entity |
| Predicate | 직업적정체성 |
P147206
|
FINISHED |
| Object | 스크린과 브라운관을 오가는 배우 |
—
|
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: 스크린과 브라운관을 오가는 배우 | Statement: [박해수, 직업적정체성, 스크린과 브라운관을 오가는 배우]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 직업적정체성 Context triple: [박해수, 직업적정체성, 스크린과 브라운관을 오가는 배우]
-
A.
occupationAspiration
Indicates a person's desired or intended future occupation or career goal.
-
B.
isOccupationalFormOf
Indicates that one occupation is a specific form, variant, or specialization of another, more general occupation.
-
C.
professionAttribute
Indicates that a specific attribute, quality, or characteristic is associated with a given profession.
-
D.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
E.
professionalCompetence
Indicates that one entity possesses the necessary skills, knowledge, and ability to perform a professional role or task to an acceptable standard in relation to another entity or context.
- F. None of above. chosen
Provenance (4 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_69e11e3c4c5c81908d336165816b12e0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a2d8064819094d27ef9f15c6a1f |
completed | April 28, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69e71b41555881909b8e22718974d527 |
completed | April 21, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e7222d208c819098b12c13e31af629 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:34 p.m.