Triple
T18392477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Çeltik |
E449767
|
entity |
| Predicate | transportCountryRoadNetwork |
P12181
|
FINISHED |
| Object | Turkey road network in Konya Province |
—
|
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: Turkey road network in Konya Province | Statement: [Çeltik, transportCountryRoadNetwork, Turkey road network in Konya Province]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportCountryRoadNetwork Context triple: [Çeltik, transportCountryRoadNetwork, Turkey road network in Konya Province]
-
A.
roadNetworkCountryCode
Indicates the country code associated with the road network in which the related entity or segment is located.
-
B.
roadAccessCountryNetwork
Indicates that there exists a road-based transportation connection or accessibility between a country and a broader network of locations or routes.
-
C.
transportNetwork
chosen
Indicates a relationship where infrastructure or services enable the movement of people or goods between different locations.
-
D.
hasRoadNetworkType
Indicates the type or classification of road network associated with or present in an entity.
-
E.
roadNetworkContext
Indicates the contextual relationship between elements within a road network, such as how roads, intersections, and related infrastructure are organized or interact.
- 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_69d8b9fab8a8819086a9ddc0871715e0 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e518435cf481908393c1eb2b4ba659 |
completed | April 19, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69e44ff1f92c8190afbb8e85d12bf2a9 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:46 a.m.