Triple
T36675559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden State (passenger train) |
E905532
|
entity |
| Predicate | routeViaRegion |
P51005
|
FINISHED |
| Object | Midwest |
—
|
NE NERFINISHED |
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: Midwest | Statement: [Golden State (passenger train), routeViaRegion, Midwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routeViaRegion Context triple: [Golden State (passenger train), routeViaRegion, Midwest]
-
A.
routeRegion
chosen
Indicates that a route is located within, passes through, or is associated with a particular geographic region.
-
B.
languageRegionsAlongRoute
Indicates the languages spoken in the geographic regions that lie along a specified route.
-
C.
routeOf
Indicates that one entity is the path, course, or trajectory taken or followed by another entity (such as a vehicle, shipment, or signal).
-
D.
routeVia
Indicates that a connection, path, or communication between two points is established or carried out through an intermediate location, node, or channel.
-
E.
transportationRegion
Indicates that one entity serves as, or is associated with, a geographic region relevant to the transportation activities or coverage of another entity.
- 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_69f76e7011dc819082b324f18b756a1b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c7a1e71081909b8eebef98c15437 |
completed | May 3, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:12 p.m.