Triple
T23129697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spine Care Institute |
E577132
|
entity |
| Predicate | servesPatientPopulation |
P17586
|
FINISHED |
| Object | adult patients with spine-related conditions |
—
|
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: adult patients with spine-related conditions | Statement: [Spine Care Institute, servesPatientPopulation, adult patients with spine-related conditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesPatientPopulation Context triple: [Spine Care Institute, servesPatientPopulation, adult patients with spine-related conditions]
-
A.
hasServiceAreaPopulation
Indicates that an entity has a service area characterized by a specific population size or count.
-
B.
servesPopulationCentre
Indicates that one entity provides services or functions in support of a particular population centre.
-
C.
targetedPopulation
chosen
Indicates the group of individuals or entities that an action, intervention, or effect is specifically directed toward.
-
D.
hasHealthcareServicesIn
Indicates that a healthcare provider or organization offers or operates healthcare services within a specified location or area.
-
E.
treatsPatientsFrom
Indicates that a healthcare provider gives medical treatment or services to patients originating from a particular location or group.
- 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_69e245f7b0e481909c473ff4e6a54e2c |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e8671f48190887e57d5723e49c1 |
completed | April 29, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_69ef89f83b108190aaaa1db6221fc163 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4 p.m.