Triple
T26521281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roosevelt Boulevard (US 1) |
E669960
|
entity |
| Predicate | hasNumberOfRoadwayTypes |
P26277
|
FINISHED |
| Object | inner express lanes and outer local lanes |
—
|
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: inner express lanes and outer local lanes | Statement: [Roosevelt Boulevard (US 1), hasNumberOfRoadwayTypes, inner express lanes and outer local lanes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfRoadwayTypes Context triple: [Roosevelt Boulevard (US 1), hasNumberOfRoadwayTypes, inner express lanes and outer local lanes]
-
A.
numberOfRoadways
Indicates the count of distinct roadways associated with or present at a given entity or location.
-
B.
hasRoadNetworkType
Indicates the type or classification of road network associated with or present in an entity.
-
C.
hasRoadway
Indicates that one location or area is connected to another by a road or roadway infrastructure.
-
D.
hasRoadConfiguration
chosen
Indicates that there exists a specific arrangement or layout of roads associated with or characterizing an entity.
-
E.
hasNumberOfSlipRoads
Indicates the number of slip roads (on/off ramps) associated with a particular road segment or junction.
- 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_69eeb31b6dcc8190b30632dc3928a0c0 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f71996e1a48190ac59a1d66d7c44e8 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
Created at: April 27, 2026, 1:28 a.m.