Triple
T17816731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bönigen |
E444864
|
entity |
| Predicate | hasLake |
P1025
|
FINISHED |
| Object | Lake Brienz |
—
|
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: Lake Brienz | Statement: [Bönigen, hasLake, Lake Brienz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Brienz Context triple: [Bönigen, hasLake, Lake Brienz]
-
A.
Lake Brienz
chosen
Lake Brienz is a deep, turquoise-colored alpine lake in central Switzerland, renowned for its dramatic mountain scenery and crystal-clear waters.
-
B.
Lake Thun
Lake Thun is a large alpine lake in the Bernese Oberland region of Switzerland, renowned for its scenic mountain backdrop, historic lakeside towns, and popular boating and water sports.
-
C.
Lake Sarnen
Lake Sarnen is a scenic alpine lake in the canton of Obwalden in central Switzerland, known for its clear waters and surrounding mountain landscapes.
-
D.
Oeschinen Lake
Oeschinen Lake is a scenic alpine lake in the Bernese Oberland region of Switzerland, renowned for its turquoise waters, dramatic mountain backdrop, and outdoor recreation opportunities.
-
E.
Lake Lucerne
Lake Lucerne is a residential community in Miami Gardens, Florida, known for its suburban character within the Miami metropolitan area.
- 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4887f7d048190b6d813b9f0fab3e7 |
completed | April 19, 2026, 7:47 a.m. |
Created at: April 10, 2026, 10:14 a.m.