Triple
T1762614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M2 motorway |
E38689
|
entity |
| Predicate | hasCarriageways |
P22311
|
FINISHED |
| Object | two |
—
|
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: two | Statement: [M2 motorway, hasCarriageways, two]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarriageways Context triple: [M2 motorway, hasCarriageways, two]
-
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.
roadwayCarries
Indicates that a roadway serves as a route that supports or conveys a particular transportation facility, traffic flow, or designated use.
-
C.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
D.
hasExpresswaySection
Indicates that an entity includes, contains, or is associated with a specific section or segment of an expressway.
-
E.
hasMajorHighway
Indicates that a location or area is served by or directly connected to a major highway route.
- 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_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab173936b4819097332ee185996bbd |
completed | March 6, 2026, 6:04 p.m. |
| PD | Predicate disambiguation | batch_69aa61c9e06c819085489e00cfe72153 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.