Triple
T11757936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweet Briar, Virginia |
E279573
|
entity |
| Predicate | hasCampusDominantLandUse |
P43475
|
FINISHED |
| Object | educational |
—
|
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: educational | Statement: [Sweet Briar, Virginia, hasCampusDominantLandUse, educational]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCampusDominantLandUse Context triple: [Sweet Briar, Virginia, hasCampusDominantLandUse, educational]
-
A.
isMajorCampusArea
Indicates that a given area constitutes a primary or significant part of a campus.
-
B.
hasLandUsePressure
Indicates that an area or entity is subject to demands or stresses from human or other uses of land that may affect its condition or availability.
-
C.
hasLandUseCharacter
chosen
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
D.
hasCampusCity
Indicates that an educational institution or campus is located in a particular city.
-
E.
hasCampusOn
Indicates that an institution or organization maintains a campus located on a specified geographic area or site.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a5220f148190ae60d1941a579ab6 |
completed | April 10, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69d88a829fe481909cc5431de7d6058e |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.