Triple
T4252991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Junction 1a of M60 motorway |
E95900
|
entity |
| Predicate | hasCarriagewayDirection |
P4069
|
FINISHED |
| Object | clockwise |
—
|
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: clockwise | Statement: [Junction 1a of M60 motorway, hasCarriagewayDirection, clockwise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarriagewayDirection Context triple: [Junction 1a of M60 motorway, hasCarriagewayDirection, clockwise]
-
A.
hasCarriagewayType
Indicates the specific structural or functional type of carriageway associated with a road segment (e.g., single, dual, or other carriageway configurations).
-
B.
hasTrafficDirection
chosen
Indicates that there is a specified flow or orientation of traffic associated with an entity (such as a road, lane, or route).
-
C.
hasStreetDirection
Indicates that a street or road segment is associated with a specific directional orientation (e.g., northbound, east-west).
-
D.
crossingDirection
Indicates the direction in which one entity moves or passes across another reference point, boundary, or path.
-
E.
hasRouteDirection
Indicates that a specified route is associated with a particular travel direction (e.g., inbound, outbound, northbound).
- 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_69b3453f759881909b91f01a1e82c036 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34ebc98e08190915ac309a51ef87f |
completed | March 12, 2026, 11:39 p.m. |
| PD | Predicate disambiguation | batch_69b347f73e008190a908a48ef389945a |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:06 p.m.