Triple
T18439651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 3rd Avenue (Seattle) |
E450491
|
entity |
| Predicate | hasTrafficPriority |
P63603
|
FINISHED |
| Object | transit-priority street |
—
|
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: transit-priority street | Statement: [3rd Avenue (Seattle), hasTrafficPriority, transit-priority street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrafficPriority Context triple: [3rd Avenue (Seattle), hasTrafficPriority, transit-priority street]
-
A.
hasTramPriority
Indicates that trams are given precedence over other traffic in movement or right-of-way.
-
B.
hasTrafficMode
Indicates the mode or type of traffic associated with or applicable to an entity (e.g., pedestrian, vehicular, public transit).
-
C.
hasPriorityAtJunctions
chosen
Indicates that one entity is granted precedence or right-of-way over others when passing through junctions or intersections.
-
D.
hasPrimaryTrafficType
Indicates that an entity is associated with a main or predominant type of traffic it handles or is designed for.
-
E.
hasTrafficFeature
Indicates that an entity possesses or is associated with a specific traffic-related characteristic, element, or infrastructure feature.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c0fda908190901a108fb9982a2d |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:30 a.m.