Triple
T23014787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Havel lakes |
E573001
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Kleiner Wannsee |
—
|
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: Kleiner Wannsee | Statement: [Havel lakes, hasPart, Kleiner Wannsee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kleiner Wannsee Context triple: [Havel lakes, hasPart, Kleiner Wannsee]
-
A.
Wannsee
Wannsee is a lakeside district in southwestern Berlin, Germany, known for its villa colonies, recreational waterfront, and as the site of the infamous 1942 Wannsee Conference.
-
B.
Großer Wannsee lake
chosen
Großer Wannsee lake is a popular recreational lake in southwestern Berlin, known for its beaches, sailing, and proximity to historically significant sites.
-
C.
Pulhof
Pulhof is a residential neighborhood in the Antwerp district of Berchem, Belgium, known for its quiet streets and urban character.
-
D.
Schottensee
Schottensee is a picturesque alpine lake in the Pizol region of the Swiss Alps, popular with hikers for its clear blue waters and scenic mountain backdrop.
-
E.
Halensee
Halensee is a railway station in Berlin that serves the city's circular Ringbahn line, connecting the Halensee district to the wider urban rail network.
- 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e3c0e08190a7ac747b056ec3ca |
completed | April 29, 2026, 4:06 a.m. |
Created at: April 17, 2026, 3:51 p.m.