Triple
T6939187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A1(M) |
E160628
|
entity |
| Predicate | hasLaneCountTypical |
P18336
|
FINISHED |
| Object | 2 or 3 lanes each direction |
—
|
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: 2 or 3 lanes each direction | Statement: [A1(M), hasLaneCountTypical, 2 or 3 lanes each direction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaneCountTypical Context triple: [A1(M), hasLaneCountTypical, 2 or 3 lanes each direction]
-
A.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
B.
laneCount
chosen
Indicates the number of parallel lanes associated with a given road or roadway segment.
-
C.
hasTrackLanes
Indicates that an entity (such as a road or track) includes one or more designated lanes for vehicle or train movement.
-
D.
hasLaneConfigurations
Indicates that an entity is associated with one or more specific arrangements or patterns of lanes (e.g., number, type, or direction of lanes).
-
E.
hasDedicatedLanes
Indicates that specific lanes within a route or roadway are reserved exclusively for a particular type of traffic or use.
- 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_69c6884f3db4819080ad65da69386206 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e0c74fe48190aeaa018631e52ef6 |
completed | March 27, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bd5a388190a57a96d925696ff6 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:28 p.m.