Triple
T210388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor of Dentistry (Dr. med. dent.) |
E4703
|
entity |
| Predicate | thesisType |
P9143
|
FINISHED |
| Object | clinical dissertation |
—
|
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: clinical dissertation | Statement: [Doctor of Dentistry (Dr. med. dent.), thesisType, clinical dissertation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thesisType Context triple: [Doctor of Dentistry (Dr. med. dent.), thesisType, clinical dissertation]
-
A.
doctoralThesisTitle
Indicates the title associated with a person's doctoral thesis.
-
B.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
C.
scholarshipType
Indicates the specific category or kind of scholarship associated with an entity.
-
D.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
E.
titleType
Indicates the specific category or kind of title associated with an entity (e.g., whether it is a main title, alternative title, working title, etc.).
- 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.