Triple
T16257189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aberdeen bus station |
E394661
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | FlixBus |
E270812
|
NE 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: FlixBus | Statement: [Aberdeen bus station, operator, FlixBus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FlixBus Context triple: [Aberdeen bus station, operator, FlixBus]
-
A.
FlixBus
chosen
FlixBus is a long-distance intercity bus company offering low-cost coach travel across numerous cities in North America and Europe.
-
B.
OurBus
OurBus is a technology-driven intercity bus company that offers affordable, reservation-based coach services across various U.S. routes.
-
C.
DB Regio Bus
DB Regio Bus is the regional and local bus transport division of Deutsche Bahn, operating extensive bus services across Germany.
-
D.
BoltBus
BoltBus is a low-cost intercity bus service in the United States and Canada known for offering budget-friendly fares and modern onboard amenities.
-
E.
Megabus
Megabus is a low-cost intercity coach service known for operating long-distance bus routes across major cities in North America and Europe.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2459b1624819086bf681075097235 |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a000eebcfe481909822290d3a7b361c |
completed | May 10, 2026, 4:51 a.m. |
Created at: April 10, 2026, 5:04 a.m.