Triple
T1049553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsche Bahn |
E22662
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object | DB Station&Service |
E54321
|
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 Station&Service | Statement: [Deutsche Bahn, subsidiary, DB Station&Service]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DB Station&Service Context triple: [Deutsche Bahn, subsidiary, DB Station&Service]
-
A.
DB Station&Service
chosen
DB Station&Service is a subsidiary of Deutsche Bahn responsible for managing and operating railway stations across Germany.
-
B.
NS Stations
NS Stations is a Dutch company responsible for managing and developing railway stations and related facilities across the Netherlands.
-
C.
Reservoir station
Reservoir station is a light rail stop on Boston’s MBTA Green Line that serves the D branch near Cleveland Circle in Brookline.
-
D.
Jubany Station
Jubany Station is an Argentine Antarctic research base located on King George Island near the Antarctic Peninsula, supporting scientific studies in fields such as glaciology, biology, and atmospheric science.
-
E.
King station
King station is a downtown Toronto subway station on the TTC network serving the Financial District and nearby attractions.
- 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.