Triple
T14897389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maniwaki |
E359912
|
entity |
| Predicate | hasRuralServiceFunction |
P80865
|
FINISHED |
| Object | health services |
—
|
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 services | Statement: [Maniwaki, hasRuralServiceFunction, health services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuralServiceFunction Context triple: [Maniwaki, hasRuralServiceFunction, health services]
-
A.
hasRuralServiceTown
Indicates that a rural area or region is associated with, and typically receives services from, a specific town that functions as its service center.
-
B.
isRuralServiceTown
Indicates that a town functions primarily as a service and support center for surrounding rural or agricultural areas.
-
C.
servesRuralArea
chosen
Indicates that an entity provides services or support specifically to people or communities located in rural areas.
-
D.
hasRuralLocality
Indicates that an entity possesses, includes, or is associated with a rural locality (such as a village, hamlet, or countryside settlement) within its scope or jurisdiction.
-
E.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded6084574819098033a9723f3e1c4 |
completed | April 15, 2026, 12:04 a.m. |
| PD | Predicate disambiguation | batch_69de9a4a14a88190951bb8f4c60bd37b |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:11 a.m.