Triple
T592828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M25 motorway |
E17312
|
entity |
| Predicate | hasLaneCount |
P2128
|
FINISHED |
| Object | up to 6 lanes each way in some sections |
—
|
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: up to 6 lanes each way in some sections | Statement: [M25 motorway, hasLaneCount, up to 6 lanes each way in some sections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaneCount Context triple: [M25 motorway, hasLaneCount, up to 6 lanes each way in some sections]
-
A.
hasLanes
chosen
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
B.
hasExpresswaySection
Indicates that an entity includes, contains, or is associated with a specific section or segment of an expressway.
-
C.
hasTrafficDirection
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
-
D.
hasApproachRoad
Indicates that one entity is connected to or accessed by another entity via an approach road leading to it.
-
E.
hasNumberOfArches
Indicates the relationship specifying how many arches are present in or associated with a given entity.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bbcaf5c81908de4e27096d3da13 |
completed | March 1, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69a494cd7d3c8190af008acf34a2293b |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.