Triple
T15224506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F Market & Wharves historic streetcar line |
E363842
|
entity |
| Predicate | vehicleCollection |
P60619
|
FINISHED |
| Object | historic streetcars from multiple cities |
—
|
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: historic streetcars from multiple cities | Statement: [F Market & Wharves historic streetcar line, vehicleCollection, historic streetcars from multiple cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleCollection Context triple: [F Market & Wharves historic streetcar line, vehicleCollection, historic streetcars from multiple cities]
-
A.
hasVehicleCollection
chosen
Indicates that an entity possesses or maintains a set or collection of vehicles.
-
B.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
C.
vehicleName
Indicates the specific name or designation assigned to a vehicle.
-
D.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
E.
carModel
Indicates the specific model designation of a car within a particular make or brand.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078a9318819081db3b7bcc28e04f |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:12 a.m.