Triple
T210406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor of Dentistry (Dr. med. dent.) |
E4703
|
entity |
| Predicate | professionalTitleAfterCompletion |
P9145
|
FINISHED |
| Object | Dr. med. dent. |
—
|
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: Dr. med. dent. | Statement: [Doctor of Dentistry (Dr. med. dent.), professionalTitleAfterCompletion, Dr. med. dent.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalTitleAfterCompletion Context triple: [Doctor of Dentistry (Dr. med. dent.), professionalTitleAfterCompletion, Dr. med. dent.]
-
A.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
B.
careerStart
Indicates the point in time when an entity begins its professional career or main occupational activity.
-
C.
describesCareerOf
Indicates that one entity provides a description or characterization of the professional career of another entity.
-
D.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
-
E.
positionInWork
Indicates the specific role, rank, or placement an entity holds within a larger work or structured composition.
- F. None of above. chosen
Provenance (4 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b4f71b88190866c8262922ae204 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25d3463648190ac716d7475378536 |
completed | Feb. 28, 2026, 3:12 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.