Triple
T20314517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DB Regio Bus |
E510343
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | DB Regio Bus |
—
|
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: DB Regio Bus | Statement: [DB Regio Bus, hasAbbreviation, DB Regio Bus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DB Regio Bus Context triple: [DB Regio Bus, hasAbbreviation, DB Regio Bus]
-
A.
DB Regio Bus
chosen
DB Regio Bus is the regional and local bus transport division of Deutsche Bahn, operating extensive bus services across Germany.
-
B.
FlixBus
FlixBus is a long-distance intercity bus company offering low-cost coach travel across numerous cities in North America and Europe.
-
C.
OurBus
OurBus is a technology-driven intercity bus company that offers affordable, reservation-based coach services across various U.S. routes.
-
D.
TMB Bus Turístic app
The TMB Bus Turístic app is a mobile application that helps users plan, navigate, and access information about Barcelona’s official tourist bus routes and services.
-
E.
Tisséo bus network
The Tisséo bus network is the public bus system serving Toulouse and its metropolitan area in southwestern France, integrated with the city's metro and tram services.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c7491c8190961113c4283b10b0 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e67745e2448190b5611382fe338bb2 |
completed | April 20, 2026, 6:58 p.m. |
Created at: April 16, 2026, 11:19 a.m.