Triple
T19481410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matten bei Interlaken |
E487392
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Unterseen |
—
|
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: Unterseen | Statement: [Matten bei Interlaken, locatedNear, Unterseen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unterseen Context triple: [Matten bei Interlaken, locatedNear, Unterseen]
-
A.
Unterseen
chosen
Unterseen is a historic Swiss town in the Bernese Oberland, situated near Interlaken at the confluence of the Aare and Lombach rivers with views of the surrounding Alps.
-
B.
Unterer See
Unterer See is a small lake located in the town of Böblingen in the German state of Baden-Württemberg.
-
C.
Mapraggsee
Mapraggsee is an artificial reservoir lake in the municipality of Pfäfers in the canton of St. Gallen, Switzerland, primarily used for hydroelectric power generation.
-
D.
Hintersee
Hintersee is a small Austrian municipality in the state of Salzburg, known for its scenic alpine landscapes and nearby mountain lake.
-
E.
Beetzsee
Beetzsee is a long, narrow lake in the German state of Brandenburg, known for its scenic waters and recreational activities such as rowing and boating.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e634393b8081909f5e4c38b2f1a9b7 |
completed | April 20, 2026, 2:12 p.m. |
Created at: April 10, 2026, 1:39 p.m.