Triple
T24026355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arizona College of Optometry |
E594970
|
entity |
| Predicate | professionPreparedFor |
P154912
|
FINISHED |
| Object | optometrist |
—
|
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: optometrist | Statement: [Arizona College of Optometry, professionPreparedFor, optometrist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionPreparedFor Context triple: [Arizona College of Optometry, professionPreparedFor, optometrist]
-
A.
professionalCategory
Indicates the classification of an entity according to its professional field, role, or occupational domain.
-
B.
professionAttribute
Indicates that a specific attribute, quality, or characteristic is associated with a given profession.
-
C.
professionalOutcome
Indicates the resulting professional status, achievement, or consequence that arises from a person’s work-related actions, experiences, or decisions.
-
D.
professionalWins
Indicates that one entity has achieved a certain number of victories or successes in a professional context, such as in a career, competition, or formal domain.
-
E.
professionalBase
Indicates that one entity serves as the primary professional location, organization, or base of operations for another entity.
- 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_69e288be2c288190a3a46006945557f7 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d76c083c819090784ecb42effbae |
completed | April 29, 2026, 10:03 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 9:54 p.m.