Triple
T14265805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BVG |
E353639
|
entity |
| Predicate | mobileApp |
P14571
|
FINISHED |
| Object | BVG Fahrinfo |
E353639
|
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: BVG Fahrinfo | Statement: [BVG, mobileApp, BVG Fahrinfo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BVG Fahrinfo Context triple: [BVG, mobileApp, BVG Fahrinfo]
-
A.
RegionalBahn
RegionalBahn is a category of regional passenger trains in Germany that provide relatively frequent, short- to medium-distance services connecting cities and smaller towns.
-
B.
Bonn public transport network
The Bonn public transport network is an integrated system of buses, trams, and regional trains serving the city of Bonn and its surrounding districts in Germany.
-
C.
Frankfurt public transport network
The Frankfurt public transport network is an integrated system of trams, buses, S-Bahn, and U-Bahn services that provides comprehensive urban and regional mobility across Frankfurt and its surrounding areas.
-
D.
BVG
chosen
BVG is Berlin’s main public transport company, operating the city’s U-Bahn, trams, buses, and ferries.
-
E.
HAFAS: GOS
HAFAS: GOS is the public transport timetable system code used to identify Goslar railway station in Germany.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6357a8188190ba518a486521052b |
completed | April 14, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd326551b08190ae8fe220a6422339 |
completed | May 8, 2026, 12:46 a.m. |
Created at: April 10, 2026, 1:09 a.m.