Triple
T6704590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yessentuki |
E152967
|
entity |
| Predicate | hasHealthcareInfrastructure |
P72534
|
FINISHED |
| Object | sanatoriums |
—
|
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: sanatoriums | Statement: [Yessentuki, hasHealthcareInfrastructure, sanatoriums]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHealthcareInfrastructure Context triple: [Yessentuki, hasHealthcareInfrastructure, sanatoriums]
-
A.
hasPublicHealthInfrastructure
Indicates that an entity possesses systems, facilities, and organizational structures dedicated to protecting and promoting public health.
-
B.
hasMedicalCenter
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
C.
healthSystem
Indicates a relationship where an entity functions as, belongs to, or is managed within a particular health care system or network.
-
D.
hasHealthcareProvider
Indicates that one entity receives healthcare services or medical oversight from another entity acting as its healthcare provider.
-
E.
numberOfHospitals
Indicates the total count of hospitals associated with a given entity or within a specified 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_69c68807adbc8190b8632df42b39eda0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d16897e48190b43eda2206b14d6a |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d089c7488190a00853fb12f53b2a |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d1668a7c8190ae93951f9ba2df10 |
completed | March 27, 2026, 6:50 p.m. |
Created at: March 27, 2026, 2:06 p.m.