Triple
T15046019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Staaken |
E379226
|
entity |
| Predicate | hasRoadConnection |
P385
|
FINISHED |
| Object | Bundesstraße 5 |
E1085138
|
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: Bundesstraße 5 | Statement: [Staaken, hasRoadConnection, Bundesstraße 5]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bundesstraße 5 Context triple: [Staaken, hasRoadConnection, Bundesstraße 5]
-
A.
Bundesstraße 5
chosen
Bundesstraße 5 is a major German federal highway that runs north–south through several states, connecting key cities such as Husum, Hamburg, and Frankfurt (Oder).
-
B.
Bundesstraße 50
Bundesstraße 50 is a German federal highway in Rhineland-Palatinate that serves as an important east–west route across the Hunsrück region.
-
C.
Bundesstraße 59
Bundesstraße 59 is a German federal highway in North Rhine-Westphalia that connects several towns and cities, serving as an important regional traffic route.
-
D.
Bundesstraße 9
Bundesstraße 9 is a major German federal highway running along the western part of the country, connecting numerous cities and towns near the Rhine.
-
E.
Bundesstraße 3
Bundesstraße 3 is a major German federal highway running north–south through several states and connecting numerous cities and towns.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded830c3c08190a87b81abbbb75377 |
completed | April 15, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9de73614819098b7a88624407d0e |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 3 a.m.