Triple
T11934748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nonfiction Writing Program |
E284009
|
entity |
| Predicate | academicDegreeType |
P11450
|
FINISHED |
| Object | Master of Fine Arts |
—
|
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: Master of Fine Arts | Statement: [Nonfiction Writing Program, academicDegreeType, Master of Fine Arts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicDegreeType Context triple: [Nonfiction Writing Program, academicDegreeType, Master of Fine Arts]
-
A.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
B.
academicType
chosen
Indicates the specific academic category or classification associated with an entity (such as a work, program, or role).
-
C.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
D.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
E.
eligibleDegree
Indicates that an academic degree qualifies its holder to be considered eligible for a particular program, position, or requirement.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90306fcf48190a963d2d1932288d1 |
completed | April 10, 2026, 2:02 p.m. |
| PD | Predicate disambiguation | batch_69d8bb3af0188190bfb22be5c97b3349 |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:45 p.m.