Triple
T21937312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middle College |
E541724
|
entity |
| Predicate | typicalCampusType |
P110
|
FINISHED |
| Object | community college campus |
—
|
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: community college campus | Statement: [Middle College, typicalCampusType, community college campus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCampusType Context triple: [Middle College, typicalCampusType, community college campus]
-
A.
campusType
chosen
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
-
B.
campusOfUniversityType
Indicates that a campus belongs to, is part of, or is categorized under a particular type of university.
-
C.
campusCategory
Indicates the classification or type assigned to a campus within a broader organizational or geographic system.
-
D.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
E.
campusAreaType
Indicates the classification of a campus area according to its type or functional category.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1241c909c81908644eb73baa9def1 |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f5efc208819091ed2cf6841fa600 |
completed | April 21, 2026, 3:58 a.m. |
Created at: April 16, 2026, 7:55 p.m.