Triple
T29626855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siberian State Medical University |
E755165
|
entity |
| Predicate | hasClinicalBase |
P181665
|
FINISHED |
| Object | teaching hospitals in Tomsk |
—
|
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: teaching hospitals in Tomsk | Statement: [Siberian State Medical University, hasClinicalBase, teaching hospitals in Tomsk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClinicalBase Context triple: [Siberian State Medical University, hasClinicalBase, teaching hospitals in Tomsk]
-
A.
clinicalBaseOf
Indicates that one clinical entity serves as the foundational basis or underlying source for another clinical entity (such as a diagnosis, assessment, or decision).
-
B.
hasClinicalService
Indicates that an entity provides, offers, or is associated with a specific clinical service.
-
C.
hasClinicalCandidate
Indicates that a substance or compound has progressed to and been designated as a clinical candidate for therapeutic development.
-
D.
hasClinicalUnit
Indicates that an entity is associated with or belongs to a specific clinical unit or department within a healthcare setting.
-
E.
hasClinicalAssessment
Indicates that a subject is associated with, or has undergone, a specific clinical assessment or evaluation.
- 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_69f0ef86b6ec8190a87fff07fd983b1e |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f7805c25dc8190b9977c561ba15975 |
completed | May 3, 2026, 5:05 p.m. |
Created at: April 28, 2026, 6:38 p.m.