Triple
T25059182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Connecticut Avenue |
E627607
|
entity |
| Predicate | hasBikewayFeatures |
P1709
|
FINISHED |
| Object | some segments with bike lanes or shared 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: some segments with bike lanes or shared lanes | Statement: [Connecticut Avenue, hasBikewayFeatures, some segments with bike lanes or shared lanes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBikewayFeatures Context triple: [Connecticut Avenue, hasBikewayFeatures, some segments with bike lanes or shared lanes]
-
A.
hasBicycleFacilities
chosen
Indicates that appropriate bicycle-related infrastructure or amenities are available at or associated with the subject.
-
B.
bikeway
Indicates that there is a designated path or route intended primarily for bicycle travel between locations.
-
C.
hasBikewayTerminus
Indicates that a bikeway ends, terminates, or has its final point at the referenced location or entity.
-
D.
bicyclesAllowed
Indicates that bicycles are permitted to use or access a particular route, area, or facility.
-
E.
hasBicyclePolicy
Indicates that there exists a specific policy or set of rules governing the use, storage, or management of bicycles in relation to the subject.
- 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_69e2ff2c45f48190afa28369f1df6786 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 6:09 a.m.