Triple
T4010254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanbrugh College |
E90626
|
entity |
| Predicate | campusPosition |
P36352
|
FINISHED |
| Object | central campus location |
—
|
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: central campus location | Statement: [Vanbrugh College, campusPosition, central campus location]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusPosition Context triple: [Vanbrugh College, campusPosition, central campus location]
-
A.
campusRole
Indicates the specific position, function, or capacity an individual holds within a campus or academic institution.
-
B.
collegePosition
Indicates the role, title, or position an individual holds within a college or university.
-
C.
isPartOfCampus
chosen
Indicates that one place, facility, or area is located within and belongs to a larger campus.
-
D.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
-
E.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaec08dc8190a341809059554f84 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fa6fec81909b1190ecbba61410 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:34 p.m.