Triple
T210372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor of Dentistry (Dr. med. dent.) |
E4703
|
entity |
| Predicate | academicTitleAbbreviation |
P9141
|
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.), academicTitleAbbreviation, Dr. med. dent.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academicTitleAbbreviation Context triple: [Doctor of Dentistry (Dr. med. dent.), academicTitleAbbreviation, Dr. med. dent.]
-
A.
honorificTitle
Indicates that one entity serves as a formal honorific or respectful title used to address or refer to another entity.
-
B.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
C.
honorificPrefix
Indicates the formal title or respectful prefix (e.g., "Dr.", "Mr.", "Prof.") used before a person's name to denote status, role, or honor.
-
D.
confersTitle
Indicates that one entity grants or bestows an official title or designation upon another entity.
-
E.
honorificSuffix
Indicates that one entity is a respectful or formal suffix appended to another entity’s name or title.
- 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.