Triple
T3824884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DB Netz |
E88661
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | DB Netze |
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 Netze | Statement: [DB Netz, brand, DB Netze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DB Netze Context triple: [DB Netz, brand, DB Netze]
-
A.
DB Netz
chosen
DB Netz is the infrastructure division of Deutsche Bahn responsible for operating and maintaining Germany’s national railway network.
-
B.
Net 25
Net 25 is a Philippine free-to-air television network known for its news, public affairs, and family-oriented entertainment programming.
-
C.
ENIC Network
The ENIC Network is a European network of national information centres that supports the recognition of foreign qualifications and promotes fair academic mobility across countries.
-
D.
NET
NET was a U.S. public television network that served as the primary national distributor of educational and cultural programming before being succeeded by PBS.
-
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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeeb6364fc8190bf8401743f1695d5 |
completed | March 9, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fb4f41c88190b3040236462c37cc |
completed | March 14, 2026, 6:08 a.m. |
Created at: March 9, 2026, 3:17 p.m.