Triple
T2028906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A46 road |
E44470
|
entity |
| Predicate | hasDualCarriagewaySections |
P22311
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [A46 road, hasDualCarriagewaySections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDualCarriagewaySections Context triple: [A46 road, hasDualCarriagewaySections, yes]
-
A.
hasCarriagewayType
chosen
Indicates the specific structural or functional type of carriageway associated with a road segment (e.g., single, dual, or other carriageway configurations).
-
B.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
C.
hasExpresswaySection
Indicates that an entity includes, contains, or is associated with a specific section or segment of an expressway.
-
D.
hasDedicatedLanes
Indicates that specific lanes within a route or roadway are reserved exclusively for a particular type of traffic or use.
-
E.
laneCount
Indicates the number of parallel lanes associated with a given road or roadway segment.
- 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_69a889144f2481909932f0746a93023d |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9136f888190b0fd03530e9eda1e |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb7a656248190ac2ced196b35bc6b |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:38 p.m.