Triple
T22582883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M-Line Streetcar |
E544610
|
entity |
| Predicate | ridershipCategory |
P84828
|
FINISHED |
| Object | local riders |
—
|
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: local riders | Statement: [M-Line Streetcar, ridershipCategory, local riders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ridershipCategory Context triple: [M-Line Streetcar, ridershipCategory, local riders]
-
A.
riderType
chosen
Indicates the category or role of a rider in relation to a ride, transport service, or vehicle (e.g., passenger, driver, courier).
-
B.
ridershipLevel
Indicates the magnitude or intensity of usage by riders or passengers for a given service, route, or system.
-
C.
rideType
Indicates the specific category or mode of transportation involved in a ride (e.g., standard, shared, premium).
-
D.
bikeCategory
Indicates the classification or type of a bicycle that an entity is associated with.
-
E.
raceCategory
Indicates the classification of an entity into a specific race or racial group within a defined categorization system.
- 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_69e11e30d05481909df915354c89f0d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f15ff26d6481908cc058f8c4b87e75 |
completed | April 29, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69ee626e6bb08190ada4dd8b48cc0c43 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:53 p.m.