Triple
T15438019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meschede |
E369819
|
entity |
| Predicate | connectedByRoad |
P11435
|
FINISHED |
| Object | Bundesstraße 7 |
E300845
|
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 7 | Statement: [Meschede, connectedByRoad, Bundesstraße 7]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bundesstraße 7 Context triple: [Meschede, connectedByRoad, Bundesstraße 7]
-
A.
Bundesstraße 7
chosen
Bundesstraße 7 is a major German federal highway running east–west across several states and connecting numerous cities and regions.
-
B.
Bundesstraße 70
Bundesstraße 70 is a federal highway in northwestern Germany that connects various towns and regions, including the locality of Wessum.
-
C.
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.
-
D.
Bundesstraße 11
Bundesstraße 11 is a major federal highway in southern Germany that runs through Bavaria, connecting Munich with the Bavarian Forest region near the Czech border.
-
E.
Bundesstraße 6
Bundesstraße 6 is a major federal highway in Germany that runs through several states and connects 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03edca064819081510bf303271062 |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21a7d44481909a26b5cc331a3259 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:21 a.m.