Triple
T735788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Medicine, University of Zurich |
E14928
|
entity |
| Predicate | academicDegreeGranted |
P6482
|
FINISHED |
| Object | Bachelor of Medicine |
—
|
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 of Medicine | Statement: [Faculty of Medicine, University of Zurich, academicDegreeGranted, Bachelor of Medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicDegreeGranted Context triple: [Faculty of Medicine, University of Zurich, academicDegreeGranted, Bachelor of Medicine]
-
A.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
B.
academicStatus
Indicates the educational or scholarly standing or level an entity holds within an academic context.
-
C.
hasDegree
chosen
Indicates that an entity possesses or has been awarded a specific academic or professional degree.
-
D.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
E.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
- 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_69a4934d9930819099eed80096b0597d |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a4fafee081909bf356854c09aaff |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.