Triple
T28843664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burlington College |
E728390
|
entity |
| Predicate | hadCampusOn |
P26464
|
FINISHED |
| Object | North Avenue, Burlington, Vermont |
—
|
NE NERFINISHED |
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: North Avenue, Burlington, Vermont | Statement: [Burlington College, hadCampusOn, North Avenue, Burlington, Vermont]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadCampusOn Context triple: [Burlington College, hadCampusOn, North Avenue, Burlington, Vermont]
-
A.
hasCampusOn
chosen
Indicates that an institution or organization maintains a campus located on a specified geographic area or site.
-
B.
hostsCampusOf
Indicates that one entity serves as the physical location or site where another entity’s campus is situated or maintained.
-
C.
hasCollegeCampus
Indicates that an institution or organization possesses or is associated with a specific college campus as a physical or organizational site.
-
D.
hasCampusCity
Indicates that an educational institution or campus is located in a particular city.
-
E.
hasSurfaceCampus
Indicates that one entity (typically an institution) maintains a physical campus or site located on the surface of another entity (such as a planet or celestial body).
- 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_69f0319e8e7c8190b37288c8845b9dbc |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f6597535488190ba3c86bfa33bf14e |
completed | May 2, 2026, 8:07 p.m. |
| PD | Predicate disambiguation | batch_69f65762b5e481908a30ca963dcba4be |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 6:41 a.m.