Triple
T4239986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mission, Kansas |
E95387
|
entity |
| Predicate | hasRoadNetworkCharacteristic |
P26277
|
FINISHED |
| Object | grid-like local street network |
—
|
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: grid-like local street network | Statement: [Mission, Kansas, hasRoadNetworkCharacteristic, grid-like local street network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoadNetworkCharacteristic Context triple: [Mission, Kansas, hasRoadNetworkCharacteristic, grid-like local street network]
-
A.
routeNetworkCharacteristic
Indicates a relationship where a specific characteristic or property is attributed to a route within a network.
-
B.
hasRoadNetworkQuality
Indicates the assessed level or condition of the road network associated with an entity.
-
C.
isPublicRoadNetwork
Indicates that a given road network is officially designated for public use and accessible to the general public for transportation.
-
D.
hasRoadConfiguration
chosen
Indicates that there exists a specific arrangement or layout of roads associated with or characterizing an entity.
-
E.
hasRoadway
Indicates that one location or area is connected to another by a road or roadway infrastructure.
- 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_69b3453d91548190b4d4ef8fe52aa2ac |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e77fb5c8190b298818acb68ff63 |
completed | March 12, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69b347f587148190a1830503459939b6 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:05 p.m.