Triple
T13563235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eder River |
E323962
|
entity |
| Predicate | hasReservoir |
P1025
|
FINISHED |
| Object | Edersee |
E269254
|
NE FINISHED |
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: Edersee | Statement: [Eder River, hasReservoir, Edersee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edersee Context triple: [Eder River, hasReservoir, Edersee]
-
A.
Edersee
chosen
Edersee is a large artificial reservoir in northern Hesse, Germany, created by the Eder Dam and known for recreation, water sports, and its scenic surroundings.
-
B.
Möhnesee
Möhnesee is a municipality in North Rhine-Westphalia, Germany, known for its large reservoir and scenic recreational area around the Möhne River.
-
C.
Cospudener See
Cospudener See is a popular artificial lake and recreational area near Leipzig in Saxony, Germany, known for swimming, sailing, and lakeside leisure activities.
-
D.
Ziegelsee
Ziegelsee is a lake in the city of Schwerin in northern Germany, known for its scenic waterfront and role in the region’s interconnected lake system.
-
E.
Okerstausee
Okerstausee is an artificial reservoir in the Harz Mountains of Germany, popular for recreation and formed by the damming of the Oker River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb00bbe848190bb33efe2af528295 |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce5ecad88190b7c8236969d9abc7 |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 9:47 p.m.