Triple
T10234161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bassett Medical Center teaching facilities |
E243419
|
entity |
| Predicate | supportsEducationFor |
P30072
|
FINISHED |
| Object | medical students |
—
|
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 students | Statement: [Bassett Medical Center teaching facilities, supportsEducationFor, medical students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsEducationFor Context triple: [Bassett Medical Center teaching facilities, supportsEducationFor, medical students]
-
A.
hasEducationalSupportFrom
Indicates that one entity receives educational assistance, guidance, or resources from another entity.
-
B.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
C.
hasEducationServices
Indicates that one entity provides or offers educational services to another entity or within a particular context.
-
D.
offersEducationTo
chosen
Indicates that one entity provides educational services, instruction, or learning opportunities to another entity.
-
E.
requiresEducationIn
Indicates that one entity necessitates that another entity possess education or formal training in a specified field or discipline.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:21 a.m.