Triple
T14856986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Laasphe |
E349382
|
entity |
| Predicate | hasNeighbouringMunicipality |
P224
|
FINISHED |
| Object | Biedenkopf |
E836937
|
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: Biedenkopf | Statement: [Bad Laasphe, hasNeighbouringMunicipality, Biedenkopf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biedenkopf Context triple: [Bad Laasphe, hasNeighbouringMunicipality, Biedenkopf]
-
A.
Biedenkopf
chosen
Biedenkopf is a small historic town in the German state of Hesse, known for its medieval old town and hilltop castle.
-
B.
Geiersthal
Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
-
C.
Köstendorf
Köstendorf is a small Austrian municipality in the state of Salzburg, known for its rural character and proximity to the city of Salzburg.
-
D.
Bernlohe
Bernlohe is a village-level district that forms part of the town of Roth in Bavaria, Germany.
-
E.
Ochsenkopf
Ochsenkopf is one of the highest and most prominent mountains in Germany’s Fichtelgebirge, known for its ski area, hiking trails, and summit broadcasting tower.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44458ec8190be295a95f5daab14 |
completed | April 14, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fea5a421e88190a7cd359209ae2818 |
completed | May 9, 2026, 3:10 a.m. |
Created at: April 10, 2026, 1:54 a.m.