Triple
T1625261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Double First Class University Plan |
E35125
|
entity |
| Predicate | evaluationMechanism |
P750
|
FINISHED |
| Object | dynamic adjustment based on performance |
—
|
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: dynamic adjustment based on performance | Statement: [Double First Class University Plan, evaluationMechanism, dynamic adjustment based on performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: evaluationMechanism Context triple: [Double First Class University Plan, evaluationMechanism, dynamic adjustment based on performance]
-
A.
evaluationBasis
Indicates the criteria, standards, or reference framework used to judge, assess, or measure something in an evaluation process.
-
B.
assessmentMethod
chosen
Indicates the method or procedure used to evaluate, measure, or judge something.
-
C.
selectionMetric
Indicates the criterion or measure used to evaluate and choose among alternative options or candidates.
-
D.
evaluationCycle
Indicates the recurring period or sequence in which evaluations or assessments are conducted and reviewed.
-
E.
ratingSystem
Indicates a system or method used to assign evaluative scores or rankings to items, actions, or entities based on defined criteria.
- 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_69a886023194819080a3fccd6e325d0e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9431af5ac8190893133f1ae490142 |
completed | March 5, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69a907c91c888190b6ed295c1a2e0977 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.