Triple
T421519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanderbilt University |
E8112
|
entity |
| Predicate | hasCampusSize |
P53
|
FINISHED |
| Object | approximately 330 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: approximately 330 acres | Statement: [Vanderbilt University, hasCampusSize, approximately 330 acres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCampusSize Context triple: [Vanderbilt University, hasCampusSize, approximately 330 acres]
-
A.
campusSize
chosen
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
-
B.
hasCampusFeature
Indicates that a campus possesses or includes a specific physical or functional feature.
-
C.
numberOfCampuses
Indicates the total count of campuses associated with a given entity.
-
D.
isLargestCampusOf
Indicates that one campus is the largest (by size, area, or capacity) among all campuses belonging to a particular institution or organization.
-
E.
hasMainCampus
Indicates that an educational institution is primarily based at or chiefly associated with a particular campus location.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eec0e9dc81908c08b209ce5278ef |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd3b948819097d96c73d0a0f699 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.