Triple
T17847240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weißer See |
E445696
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Strandbad Weißensee |
—
|
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: Strandbad Weißensee | Statement: [Weißer See, hasPart, Strandbad Weißensee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Strandbad Weißensee Context triple: [Weißer See, hasPart, Strandbad Weißensee]
-
A.
Weissensee
Weissensee is a picturesque alpine lake and surrounding region in southern Austria, renowned for its clear waters, outdoor recreation, and unspoiled natural landscape.
-
B.
Weißensee
chosen
Weißensee is a locality in Berlin known for its historic lake, residential neighborhoods, and cultural institutions, situated within the borough of Pankow.
-
C.
Fälensee
Fälensee is a picturesque alpine lake in the Alpstein massif of northeastern Switzerland, popular for hiking and mountain scenery.
-
D.
Riegsee
Riegsee is a picturesque lake in Bavaria, Germany, known for its clear waters and scenic Alpine surroundings.
-
E.
Geiseltalsee
Geiseltalsee is a large artificial lake in Saxony-Anhalt, Germany, created by flooding a former lignite mining area and now used for recreation and nature conservation.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48ffb35248190a80a428686e06d87 |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:16 a.m.