Triple
T1049552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsche Bahn |
E22662
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object | DB Netz |
E88661
|
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: DB Netz | Statement: [Deutsche Bahn, subsidiary, DB Netz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DB Netz Context triple: [Deutsche Bahn, subsidiary, DB Netz]
-
A.
DB Netz
chosen
DB Netz is the infrastructure division of Deutsche Bahn responsible for operating and maintaining Germany’s national railway network.
-
B.
DBE
DBE is the title "Dame Commander of the Order of the British Empire," a high-ranking honor awarded in the British honours system.
-
C.
ADB
ADB is a regional multilateral development bank that promotes economic growth and cooperation in Asia and the Pacific through loans, grants, and technical assistance.
-
D.
EDB
EDB is the National Rail station code for Edinburgh Waverley, the main railway station in Edinburgh, Scotland.
-
E.
Canvas Network
Canvas Network is an online learning platform that hosts and delivers massive open online courses (MOOCs) from universities and institutions worldwide.
- 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_69a493da02e081908c13ff5e02a0fe7a |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8b2c6208190b6fdf3e93b1b1d04 |
completed | March 1, 2026, 10:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bcd3a4481908f7d9f13e3697fa9 |
completed | March 7, 2026, 2:53 p.m. |
Created at: March 1, 2026, 7:42 p.m.