Triple
T23014788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Havel lakes |
E573001
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Schlachtensee |
—
|
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: Schlachtensee | Statement: [Havel lakes, hasPart, Schlachtensee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schlachtensee Context triple: [Havel lakes, hasPart, Schlachtensee]
-
A.
Schlachtensee
chosen
Schlachtensee is a lake and popular recreational area in southwestern Berlin, known for swimming, walking trails, and its surrounding forested landscape.
-
B.
Ratzeburger See
Ratzeburger See is a large glacial lake in northern Germany known for its scenic surroundings and the town of Ratzeburg situated on an island within it.
-
C.
Wandlitzsee
Wandlitzsee is a scenic lake in Brandenburg, Germany, known for recreation, bathing, and its proximity to the village of Wandlitz.
-
D.
Schweriner See
Schweriner See is a large lake in northern Germany that surrounds and characterizes the city of Schwerin, known for its scenic shores and historic lakeside castle.
-
E.
Ostorfer See
Ostorfer See is a lake in the German state of Mecklenburg-Vorpommern, forming part of the lake landscape around the city of Schwerin.
- 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.