Triple
T33986511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Mark Craig |
E871425
|
entity |
| Predicate | hasHighStandardsFor |
P143386
|
FINISHED |
| Object | medical practice |
—
|
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: medical practice | Statement: [Dr. Mark Craig, hasHighStandardsFor, medical practice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighStandardsFor Context triple: [Dr. Mark Craig, hasHighStandardsFor, medical practice]
-
A.
hasAcademicStandard
Indicates that an entity is associated with, aligned to, or governed by a specified academic or educational standard.
-
B.
isStandardOf
Indicates that something serves as the recognized norm, reference, or benchmark by which another thing is defined, measured, or evaluated.
-
C.
hasProfessionalStandard
chosen
Indicates that an entity is subject to, or operates according to, an established professional norm, guideline, or code of practice.
-
D.
sharesAcademicStandardsWith
Indicates that two educational entities follow or adhere to the same or equivalent academic standards.
-
E.
standardsUsedIn
Indicates that certain standards are applied, referenced, or followed within a particular context, process, or entity.
- 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_69f3499e964c8190b674b03f6f791b4b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fef5cf8da881908260ec633830375d |
completed | May 9, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69fef455e40481909861c82007b79bc0 |
completed | May 9, 2026, 8:46 a.m. |
Created at: May 1, 2026, 1:50 a.m.