Triple
T2374083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Bioengineering, UC Berkeley |
E46154
|
entity |
| Predicate | isInterdisciplinary |
P18353
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Department of Bioengineering, UC Berkeley, isInterdisciplinary, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInterdisciplinary Context triple: [Department of Bioengineering, UC Berkeley, isInterdisciplinary, true]
-
A.
isMultidisciplinary
chosen
Indicates that something involves or integrates multiple distinct academic or professional disciplines in its approach or composition.
-
B.
hasSubdiscipline
Indicates that one discipline includes another, more specialized field of study as a subordinate branch.
-
C.
disciplinaryMethod
Indicates a method or approach used to discipline, correct, or control another party’s behavior.
-
D.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
E.
hasInfluenceOnDiscipline
Indicates that one entity exerts an effect, shaping force, or contributing impact on the development, direction, or state of a particular discipline.
- 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_69a88a145268819083e2736cb835c696 |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abca4d89248190be7d712d5fa8382b |
completed | March 7, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69abc59d82f08190b7c36982d1ae783d |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:56 p.m.