Triple
T14524914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R27 West Coast Road |
E340749
|
entity |
| Predicate | connectsUrbanAndRuralAreas |
P114596
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [R27 West Coast Road, connectsUrbanAndRuralAreas, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsUrbanAndRuralAreas Context triple: [R27 West Coast Road, connectsUrbanAndRuralAreas, true]
-
A.
connectsRuralCommunitiesNear
Indicates a relationship where something (such as infrastructure or services) links rural communities that are geographically close to one another.
-
B.
connectsMunicipalities
Indicates a relationship where one entity serves as a link or route that joins two or more municipalities.
-
C.
ruralCoverage
Indicates the extent to which a service, infrastructure, or resource is available or provided in rural areas.
-
D.
connectsResidentialArea
Indicates a relationship where something serves as a link or route between one residential area and another.
-
E.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea04f16f88190ba357b0f8021b46b |
completed | April 14, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c518fc08190a6ce4d8be05c4c5d |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb5ac548190932f238e37271741 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:22 a.m.