Triple
T37030571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Divriği |
E916478
|
entity |
| Predicate | hasMedicalComplex |
P10262
|
FINISHED |
| Object | Divriği Hospital |
—
|
NE NERFINISHED |
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: Divriği Hospital | Statement: [Divriği, hasMedicalComplex, Divriği Hospital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedicalComplex Context triple: [Divriği, hasMedicalComplex, Divriği Hospital]
-
A.
hasMedicalCenter
chosen
Indicates that an entity possesses, hosts, or is associated with a medical center facility.
-
B.
hasTeachingHospitalComplex
Indicates that an entity is associated with or includes a complex of facilities functioning as a teaching hospital.
-
C.
hasMedicalUnit
Indicates that an entity possesses, includes, or is associated with a medical unit (such as a clinic, department, or medical team) as part of its structure or resources.
-
D.
hasHealthcareServicesIn
Indicates that a healthcare provider or organization offers or operates healthcare services within a specified location or area.
-
E.
hasHealthcareInfrastructure
Indicates that an entity possesses facilities, systems, and resources necessary to deliver healthcare services.
- 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_69f76e92c7648190bcfa277f64c71a21 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff795d25d08190b7584c72be39d309 |
completed | May 9, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69ff78a90fbc8190a62c57456dc1d4ad |
completed | May 9, 2026, 6:10 p.m. |
Created at: May 3, 2026, 4:14 p.m.