Triple
T30603743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oliver Sacks |
E778978
|
entity |
| Predicate | medicalTraining |
P169607
|
FINISHED |
| Object | neurology residency in the United States |
—
|
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: neurology residency in the United States | Statement: [Oliver Sacks, medicalTraining, neurology residency in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medicalTraining Context triple: [Oliver Sacks, medicalTraining, neurology residency in the United States]
-
A.
medicineTeachingTransferredTo
Indicates that responsibility for teaching or instruction in medicine has been moved from one party or institution to another.
-
B.
coordinatesMedicalEducation
Indicates that one entity organizes, manages, or oversees the medical education activities or programs involving another entity.
-
C.
medicalDegree
Indicates that an individual has obtained a formal medical qualification or degree from an accredited institution.
-
D.
medicalSchool
Indicates that one entity serves as the medical school where the other entity received medical education or training.
-
E.
medicalBackground
Indicates that an entity has a history of prior medical conditions, treatments, or health-related experiences relevant to its current state or context.
- 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_69f224a21fc08190abd9d8dd9eb6bb4c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f689b47ad08190beba0baceec9341c |
completed | May 2, 2026, 11:33 p.m. |
| PD | Predicate disambiguation | batch_69f67e448a9c8190b591374d98799fe3 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f0353c88190a05b2db449abe0f4 |
completed | May 2, 2026, 10:47 p.m. |
Created at: April 29, 2026, 8:25 p.m.