Triple
T97305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Addenbrooke’s Hospital (teaching affiliation) |
E1960
|
entity |
| Predicate | teachingFocus |
P31
|
FINISHED |
| Object | undergraduate medical education |
—
|
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: undergraduate medical education | Statement: [Addenbrooke’s Hospital (teaching affiliation), teachingFocus, undergraduate medical education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachingFocus Context triple: [Addenbrooke’s Hospital (teaching affiliation), teachingFocus, undergraduate medical education]
-
A.
academicFocus
Indicates the primary field of study, discipline, or subject area that an entity concentrates on academically.
-
B.
educationalApproach
Indicates the method, strategy, or philosophy used to guide teaching and learning within an educational context.
-
C.
focusesOn
chosen
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
D.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
E.
primaryLanguageOfInstruction
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a250cb400c8190b56343bbe19b48c7 |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ebd19c48190bab291fea0ecc0c2 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.