Triple
T2426396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jones Street and Beach Street |
E53537
|
entity |
| Predicate | hasStreetcarInfrastructure |
P17788
|
FINISHED |
| Object | turnaround loop or stub tracks for F line |
—
|
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: turnaround loop or stub tracks for F line | Statement: [Jones Street and Beach Street, hasStreetcarInfrastructure, turnaround loop or stub tracks for F line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStreetcarInfrastructure Context triple: [Jones Street and Beach Street, hasStreetcarInfrastructure, turnaround loop or stub tracks for F line]
-
A.
hasStreetcarSystem
Indicates that a place possesses or is served by an operational streetcar (tram) transit system.
-
B.
hasTramway
chosen
Indicates that a location or area is served by, contains, or is connected to a tramway system.
-
C.
hasLightRailSystem
Indicates that a place possesses and operates a light rail transit system.
-
D.
hasTreeLinedStreets
Indicates that the streets in a given area are lined or bordered with trees along their sides.
-
E.
hasRailSystem
Indicates that an entity possesses or is served by a rail-based transportation 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_69ab495c44d48190b7235b23719bc3f6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc9f342e88190a430b02842ded418 |
completed | March 7, 2026, 6:47 a.m. |
| PD | Predicate disambiguation | batch_69abc5a889948190b77de4ef6ac815a8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 6, 2026, 9:42 p.m.