Triple
T31618941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Mateo Caltrain Station |
E806839
|
entity |
| Predicate | supportsFareSystem |
P197310
|
FINISHED |
| Object | Clipper card |
E38241
|
NE 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: Clipper card | Statement: [San Mateo Caltrain Station, supportsFareSystem, Clipper card]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsFareSystem Context triple: [San Mateo Caltrain Station, supportsFareSystem, Clipper card]
-
A.
hasFareIntegration
Indicates that two or more transportation services or systems share a coordinated fare structure, allowing passengers to use a single ticket or payment arrangement across them.
-
B.
fareSystemFeature
Indicates that a fare system possesses or supports a particular feature, function, or characteristic related to how fares are calculated, managed, or used.
-
C.
hasFareZoneSystem
Indicates that an entity uses or is associated with a particular fare zone system for determining travel costs or ticketing.
-
D.
hasFareCardsAccepted
chosen
Indicates that a transportation service accepts specific types of fare cards as valid payment.
-
E.
hasFareControlIntegrationSince
Indicates that a fare control system has been integrated with another system or entity starting from a specific point in time.
- F. None of above.
Provenance (4 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_69f348d7883c8190b6c13ab92b7ef076 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2b5665438c8190a00dcee088497b4a |
completed | June 12, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 30, 2026, 10:40 p.m.