Triple
T7876716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michiko Itatani |
E182873
|
entity |
| Predicate | teachingSpecialization |
P48722
|
FINISHED |
| Object | painting |
—
|
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: painting | Statement: [Michiko Itatani, teachingSpecialization, painting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachingSpecialization Context triple: [Michiko Itatani, teachingSpecialization, painting]
-
A.
definedTeaching
Indicates that one entity has formally specified or established the teaching content, method, or curriculum for another entity.
-
B.
coreTeaching
Indicates that an entity serves as a primary or foundational teaching or instructional activity for another entity.
-
C.
typeOfTeaching
Indicates the specific method or style of teaching used in an instructional context.
-
D.
taughtAs
Indicates that one entity served as a teacher or instructor for another entity in an educational or training context.
-
E.
scopeOfTeaching
chosen
Indicates the range, subjects, or areas that a teaching activity, role, or responsibility covers.
- 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39bc07208190aa452cef8ca5b0d6 |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae928e1b88190b0620f4c4f03bc7d |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:57 p.m.