Triple
T13611473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keio University School of Medicine |
E325196
|
entity |
| Predicate | hasAffiliatedFacility |
P20607
|
FINISHED |
| Object | teaching hospital |
—
|
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 hospital | Statement: [Keio University School of Medicine, hasAffiliatedFacility, teaching hospital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAffiliatedFacility Context triple: [Keio University School of Medicine, hasAffiliatedFacility, teaching hospital]
-
A.
hasAffiliatedHospital
chosen
Indicates that one entity (typically a medical professional, clinic, or organization) is formally connected or associated with a particular hospital for professional or operational purposes.
-
B.
hasSubfacility
Indicates that one facility is a subordinate or component facility within another, larger facility.
-
C.
hasFacilityLevel
Indicates the degree or tier of capability, service, or infrastructure that a particular facility possesses.
-
D.
hasFacilityType
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
E.
isPrimaryFacilityFor
Indicates that one facility serves as the main or principal location responsible for supporting or serving a particular entity or operation.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.