Triple
T10307967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadway station (Caltrain) |
E241813
|
entity |
| Predicate | servesRouteBetween |
P31354
|
FINISHED |
| Object | San Francisco and San Jose |
—
|
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: San Francisco and San Jose | Statement: [Broadway station (Caltrain), servesRouteBetween, San Francisco and San Jose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesRouteBetween Context triple: [Broadway station (Caltrain), servesRouteBetween, San Francisco and San Jose]
-
A.
servesRoute
chosen
Indicates that a service, vehicle, or provider operates along or provides transportation for a specified route.
-
B.
routeBetween
Indicates that there exists a path or connection enabling travel or communication between two locations or points.
-
C.
parallelRoute
Indicates that one route runs alongside and in the same general direction as another route without intersecting it.
-
D.
serviceRoute
Indicates that a service (such as a transport or delivery operation) follows or is assigned to a particular route.
-
E.
significantlyShortensRouteBetween
Indicates that one entity provides a connection between two others that makes the path or travel distance between them substantially shorter than alternative routes.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f4f354819080b4ed4bc61bdff6 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:46 a.m.