Triple
T24036780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College of Dental Medicine–Arizona |
E595253
|
entity |
| Predicate | offersProfessionalEducationIn |
P42231
|
FINISHED |
| Object | oral health care |
—
|
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: oral health care | Statement: [College of Dental Medicine–Arizona, offersProfessionalEducationIn, oral health care]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersProfessionalEducationIn Context triple: [College of Dental Medicine–Arizona, offersProfessionalEducationIn, oral health care]
-
A.
offersEducationIn
chosen
Indicates that an entity provides or delivers educational programs, courses, or instruction in a specified field, subject, or area.
-
B.
offersEducationTo
Indicates that one entity provides educational services, instruction, or learning opportunities to another entity.
-
C.
offersProfessionalPrograms
Indicates that an entity provides formal, career-oriented educational or training programs to others.
-
D.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
E.
offersEducationForYears
Indicates that an entity provides educational instruction or programs for a specified number of years.
- 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_69e288bf45f08190a1b6ed8cd0b9e86b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d8d5fdc48190a037cf9447309356 |
completed | April 29, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:56 p.m.