Triple
T20314565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Netinera |
E510344
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | Netinera Deutschland |
—
|
NE NERFINISHED |
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: Netinera Deutschland | Statement: [Netinera, hasAbbreviation, Netinera Deutschland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Netinera Deutschland Context triple: [Netinera, hasAbbreviation, Netinera Deutschland]
-
A.
Netinera
chosen
Netinera is a major private rail and bus transport company operating regional passenger services across Germany.
-
B.
Nete
The Nete is a river in Belgium that flows through the Flemish region and serves as one of the main tributaries forming the Rupel River.
-
C.
Netia
Netia is one of Poland’s leading telecommunications providers, offering broadband internet and related services to residential and business customers nationwide.
-
D.
NETI
NETI is the commonly used abbreviation for Novosibirsk State Technical University, a major technical higher education institution in Novosibirsk, Russia.
-
E.
Netivot
Netivot is a growing city in southern Israel known for its diverse population, religious communities, and proximity to the Gaza Strip.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c7491c8190961113c4283b10b0 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e67745e2448190b5611382fe338bb2 |
completed | April 20, 2026, 6:58 p.m. |
Created at: April 16, 2026, 11:19 a.m.