Triple
T13124590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellensburg |
E311811
|
entity |
| Predicate | hasUniversityCampusType |
P110
|
FINISHED |
| Object | public university campus town |
—
|
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: public university campus town | Statement: [Ellensburg, hasUniversityCampusType, public university campus town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUniversityCampusType Context triple: [Ellensburg, hasUniversityCampusType, public university campus town]
-
A.
hasCollegeCampus
Indicates that an institution or organization possesses or is associated with a specific college campus as a physical or organizational site.
-
B.
hasUniversityCampusArea
Indicates the total physical area occupied by a university’s campus.
-
C.
hasPublicUniversityCampus
Indicates that a public university maintains or operates a campus at the specified location.
-
D.
hasCampusOn
Indicates that an institution or organization maintains a campus located on a specified geographic area or site.
-
E.
campusType
chosen
Indicates the classification or category of a campus based on its type (e.g., main, satellite, urban, rural).
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9819946808190b41335fb1054accd |
completed | April 10, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69d98043a74c81908648e6cd0b4c7f71 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:07 p.m.