Triple
T10231198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Dental Anesthesiology |
E243342
|
entity |
| Predicate | conductsTrainingIn |
P40765
|
FINISHED |
| Object | sedation for dentistry |
—
|
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: sedation for dentistry | Statement: [Department of Dental Anesthesiology, conductsTrainingIn, sedation for dentistry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conductsTrainingIn Context triple: [Department of Dental Anesthesiology, conductsTrainingIn, sedation for dentistry]
-
A.
providesTrainingFor
chosen
Indicates that one entity delivers or conducts training activities intended to develop the skills or knowledge of another entity.
-
B.
leadsToTrainingAt
Indicates that one entity causes, results in, or serves as a pathway to another entity undergoing training.
-
C.
trainingUnder
Indicates that one entity is receiving instruction, guidance, or mentorship from another, typically in a subordinate or apprentice-like capacity.
-
D.
training
Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
-
E.
trainingLeadsTo
Indicates that a process of training results in or brings about a particular outcome, state, or effect.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:19 a.m.