Triple
T24303931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sutton Bonington |
E612477
|
entity |
| Predicate | campusSpecialism |
P104142
|
FINISHED |
| Object | agricultural sciences |
—
|
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: agricultural sciences | Statement: [Sutton Bonington, campusSpecialism, agricultural sciences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusSpecialism Context triple: [Sutton Bonington, campusSpecialism, agricultural sciences]
-
A.
campusCategory
Indicates the classification or type assigned to a campus within a broader organizational or geographic system.
-
B.
campusSector
Indicates that one location or facility is part of, or belongs to, a specific sector or zone within a campus.
-
C.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
-
D.
campusType
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
E.
institutionSpecialization
chosen
Indicates that an institution focuses on, is dedicated to, or has expertise in a particular field, domain, or area of activity.
- 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_69e2d7d91bb48190bc5377d17a85fb21 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f29224c7cc8190bd1a32318198326c |
completed | April 29, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69f1c45c6ec081908401b69424428100 |
completed | April 29, 2026, 8:42 a.m. |
Created at: April 18, 2026, 1:29 a.m.