Triple
T4258968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porter Avenue |
E96052
|
entity |
| Predicate | hasTransportationUse |
P11571
|
FINISHED |
| Object | motor vehicle traffic |
—
|
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: motor vehicle traffic | Statement: [Porter Avenue, hasTransportationUse, motor vehicle traffic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransportationUse Context triple: [Porter Avenue, hasTransportationUse, motor vehicle traffic]
-
A.
hasPublicTransportUsage
Indicates that an entity makes use of, or is associated with the use of, public transportation services.
-
B.
passesUsedForTransportation
Indicates that the passes are utilized as a means or instrument for transporting people or goods.
-
C.
hasTransportationContext
Indicates that there is a contextual relationship involving transportation modes, conditions, or circumstances relevant to the associated entities or event.
-
D.
hasTransportationSystem
Indicates that an entity possesses, operates, or is served by an organized system for transporting people or goods.
-
E.
usesTransport
chosen
Indicates that an entity employs or relies on a particular mode or means of transportation to move from one place to another.
- 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_69b3454095ac81909c2494f7ff294af1 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34f7ec4508190a5067f1112ac7dca |
completed | March 12, 2026, 11:42 p.m. |
| PD | Predicate disambiguation | batch_69b347f73e008190a908a48ef389945a |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:06 p.m.