Triple
T18217918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wheaton College (Massachusetts) |
E436212
|
entity |
| Predicate | campusSizeApproximate |
P53
|
FINISHED |
| Object | about 400 acres |
—
|
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: about 400 acres | Statement: [Wheaton College (Massachusetts), campusSizeApproximate, about 400 acres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: campusSizeApproximate Context triple: [Wheaton College (Massachusetts), campusSizeApproximate, about 400 acres]
-
A.
campusSize
chosen
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
-
B.
hasFacultySizeApprox
Indicates that an institution has an approximate number of faculty members equal to the specified value.
-
C.
hasUniversityCampusArea
Indicates the total physical area occupied by a university’s campus.
-
D.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
E.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
- 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_69d8b9103a8081908bbb0836fef10efd |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e4782db4819093baee57f34be490 |
completed | April 19, 2026, 2:19 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.