Triple
T15900111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loreto Canton |
E385561
|
entity |
| Predicate | hasHealthInfrastructureType |
P2560
|
FINISHED |
| Object | health centers |
—
|
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: health centers | Statement: [Loreto Canton, hasHealthInfrastructureType, health centers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHealthInfrastructureType Context triple: [Loreto Canton, hasHealthInfrastructureType, health centers]
-
A.
hasHealthcareInfrastructure
Indicates that an entity possesses facilities, systems, and resources necessary to deliver healthcare services.
-
B.
hasPublicHealthInfrastructure
Indicates that an entity possesses systems, facilities, and organizational structures dedicated to protecting and promoting public health.
-
C.
hasInfrastructureType
chosen
Indicates that an entity possesses or is associated with a specific category or type of infrastructure.
-
D.
hasHospitalType
Indicates that a hospital is classified as belonging to a specific type or category (e.g., general, specialized, teaching).
-
E.
hasOwnHealthSystem
Indicates that an entity operates and controls its own dedicated healthcare system, rather than relying solely on external or shared health 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:51 a.m.