Triple
T6680428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AUC |
E151963
|
entity |
| Predicate | hasAcademicFieldStrength |
P41356
|
FINISHED |
| Object | liberal 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: liberal arts | Statement: [AUC, hasAcademicFieldStrength, liberal arts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcademicFieldStrength Context triple: [AUC, hasAcademicFieldStrength, liberal arts]
-
A.
hasAcademicStrengthIn
chosen
Indicates that an entity possesses notable ability, proficiency, or strong performance in a particular academic subject or field.
-
B.
researchStrength
Indicates the degree to which an entity possesses strong capabilities, performance, or impact in conducting research.
-
C.
hasAcademicFieldGroup
Indicates that an entity is associated with, or belongs to, a particular group or category of academic fields.
-
D.
hasAcademicBackgroundIn
Indicates that an entity possesses formal education, training, or scholarly experience in a specified academic field or discipline.
-
E.
hasAcademicComponent
Indicates that something includes, involves, or is associated with an academic or educational element as part of its structure or content.
- 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_69c687f830bc81909eb8b04dbb8450b1 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c0aa8c5c8190a302b261f11b70cb |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0b6d00819086205b8ce30dd045 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:04 p.m.