Triple
T22317354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Dentistry, University of Nantes |
E551680
|
entity |
| Predicate | professionTrained |
P22559
|
FINISHED |
| Object | dentist |
—
|
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: dentist | Statement: [Faculty of Dentistry, University of Nantes, professionTrained, dentist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionTrained Context triple: [Faculty of Dentistry, University of Nantes, professionTrained, dentist]
-
A.
trainedAs
chosen
Indicates that one entity has received education or instruction to perform the role, profession, or function represented by another entity.
-
B.
professionAttribute
Indicates that a specific attribute, quality, or characteristic is associated with a given profession.
-
C.
professionalName
Indicates the formal name or title an entity uses in a professional or occupational context.
-
D.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
E.
professionalCompetence
Indicates that one entity possesses the necessary skills, knowledge, and ability to perform a professional role or task to an acceptable standard in relation to another entity or 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157543d688190a151fade71880131 |
completed | April 29, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69e73004d9e88190bb862319a5aea06b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:42 p.m.