Triple
T17421929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kander Valley |
E423637
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Reichenbach im Kandertal |
—
|
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: Reichenbach im Kandertal | Statement: [Kander Valley, containsSettlement, Reichenbach im Kandertal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reichenbach im Kandertal Context triple: [Kander Valley, containsSettlement, Reichenbach im Kandertal]
-
A.
Reichenbach im Kandertal
chosen
Reichenbach im Kandertal is a Swiss municipality in the Bernese Oberland known as a gateway to the Kander Valley and nearby alpine peaks.
-
B.
Biebelried
Biebelried is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and proximity to the Franconian wine region.
-
C.
Reichersbeuern
Reichersbeuern is a small Bavarian municipality in southern Germany known for its rural character and Alpine foothill setting.
-
D.
Villenbach
Villenbach is a small municipality in the Bavarian region of southern Germany.
-
E.
Erlbach
Erlbach is a small municipality in Bavaria, Germany, known for its rural character within the southeastern Bavarian region.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44237f2cc819083ca0e7e00d828fb |
completed | April 19, 2026, 2:47 a.m. |
Created at: April 10, 2026, 5:46 a.m.