Triple
T960287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California Zephyr |
E20719
|
entity |
| Predicate | routeSegment |
P21871
|
FINISHED |
| Object | Chicago to Denver |
—
|
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: Chicago to Denver | Statement: [California Zephyr, routeSegment, Chicago to Denver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routeSegment Context triple: [California Zephyr, routeSegment, Chicago to Denver]
-
A.
route
Indicates that one entity serves as a path or course used to travel or move between locations associated with another entity.
-
B.
routeVia
Indicates that a connection, path, or communication between two points is established or carried out through an intermediate location, node, or channel.
-
C.
routeDescription
Indicates a textual explanation or summary of the path, course, or itinerary taken between locations.
-
D.
parallelRoute
Indicates that one route runs alongside and in the same general direction as another route without intersecting it.
-
E.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
- F. None of above. chosen
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_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. |
| PDg | Predicate description generation | batch_69a4b326d9d88190913c1a892a795707 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:40 p.m.