Triple
T1220001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen's University at Kingston |
E26197
|
entity |
| Predicate | offersAcademicDegree |
P49
|
FINISHED |
| Object | bachelor's degrees |
—
|
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: bachelor's degrees | Statement: [Queen's University at Kingston, offersAcademicDegree, bachelor's degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersAcademicDegree Context triple: [Queen's University at Kingston, offersAcademicDegree, bachelor's degrees]
-
A.
offersDegree
chosen
Indicates that an institution or program provides a specific academic degree as an available qualification.
-
B.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
C.
offersFieldOfStudy
Indicates that an institution or program provides a particular field of study as an available area of academic focus.
-
D.
hasDegree
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
E.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
- 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_69a4948331fc8190b531ac9bec71c491 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be1ead088190bf44dc6ab1edf18b |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb644af08190ba25905f20adb01a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.