Triple
T960285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California Zephyr |
E20719
|
entity |
| Predicate | approximateJourneyTime |
P11363
|
FINISHED |
| Object | about 51 hours |
—
|
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: about 51 hours | Statement: [California Zephyr, approximateJourneyTime, about 51 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateJourneyTime Context triple: [California Zephyr, approximateJourneyTime, about 51 hours]
-
A.
transitFrequencyApprox
Indicates an approximate rate or regularity with which a transit event or service occurs between entities.
-
B.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
-
C.
peakDeliveryTime
Indicates the time period during which deliveries are expected to be at their highest volume or frequency.
-
D.
nearbyTransit
Indicates that one location has public transportation options situated within a short distance or easy access from it.
-
E.
rideDuration
chosen
Indicates the length of time that a ride or trip lasts from start to finish.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b412f9f48190be123e8c20f38962 |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a2e23c8190b932fe88b02f995d |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.