Triple
T8031826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mücheln (Geiseltal) |
E187001
|
entity |
| Predicate | hasLake |
P1025
|
FINISHED |
| Object | Geiseltalsee |
E731056
|
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: Geiseltalsee | Statement: [Mücheln (Geiseltal), hasLake, Geiseltalsee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geiseltalsee Context triple: [Mücheln (Geiseltal), hasLake, Geiseltalsee]
-
A.
Geiseltalsee
chosen
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.
-
B.
Würmsee
Würmsee is the historical name of the Bavarian lake now known as Starnberger See, one of Germany’s largest and most famous lakes near Munich.
-
C.
Scharmützelsee
Scharmützelsee is a popular lake in eastern Germany known for its scenic surroundings, recreational activities, and spa resorts.
-
D.
Grunewaldsee
Grunewaldsee is a popular forest lake in Berlin known for its scenic surroundings and dog-friendly bathing areas.
-
E.
Jungfernsee
Jungfernsee is a scenic lake on the outskirts of Potsdam and Berlin, known for its historic villas, palaces, and location along the former inner German border.
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ef18da48190835454a5eb969da7 |
completed | March 31, 2026, 3:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1c750c7c81908ad680f942bcbe9c |
completed | April 2, 2026, 7:36 a.m. |
Created at: March 30, 2026, 5:22 p.m.