Triple
T484289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M9 motorway |
E9839
|
entity |
| Predicate | roadNumberingScheme |
P1864
|
FINISHED |
| Object | M-road (motorway) in the United Kingdom |
—
|
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: M-road (motorway) in the United Kingdom | Statement: [M9 motorway, roadNumberingScheme, M-road (motorway) in the United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadNumberingScheme Context triple: [M9 motorway, roadNumberingScheme, M-road (motorway) in the United Kingdom]
-
A.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
B.
routeNumber
chosen
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
-
C.
roadType
Indicates the classification or category of a road based on its functional or physical characteristics.
-
D.
transportNetwork
Indicates a relationship where infrastructure or services enable the movement of people or goods between different locations.
-
E.
roadFeature
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0ba310c81909645ef7e8a20b52f |
completed | Feb. 28, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69a2edf48ec08190b85d07e194f99c49 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.