Triple
T32488706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perry Cox |
E830317
|
entity |
| Predicate | hasMedicalDegreeFrom |
P61478
|
FINISHED |
| Object | fictional medical school (unspecified in series) |
—
|
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: fictional medical school (unspecified in series) | Statement: [Perry Cox, hasMedicalDegreeFrom, fictional medical school (unspecified in series)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedicalDegreeFrom Context triple: [Perry Cox, hasMedicalDegreeFrom, fictional medical school (unspecified in series)]
-
A.
medicalDegree
Indicates that an individual has obtained a formal medical qualification or degree from an accredited institution.
-
B.
isDoctorOf
Indicates that one entity serves as the medical doctor responsible for the care or treatment of another entity.
-
C.
medicalQualificationFrom
chosen
Indicates that a person or medical professional obtained their medical qualification or degree from a specified institution or source.
-
D.
hasDoctoralDegreeFrom
Indicates that an individual holds a doctoral-level academic degree that was awarded by a specified institution.
-
E.
hasMedicalCollege
Indicates that one entity possesses, hosts, or includes a medical college as part of its organization or structure.
- 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_69f34920aa4081908d8fb0277414b911 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe91383a1c81909266e40c3c3ede6c |
completed | May 9, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69fe8fde094081908f0f121664fbb5c7 |
completed | May 9, 2026, 1:37 a.m. |
Created at: May 1, 2026, 12:58 a.m.