Triple
T7059735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Köpenick |
E164184
|
entity |
| Predicate | hasBodyOfWater |
P1778
|
FINISHED |
| Object | Müggelsee |
E157949
|
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: Müggelsee | Statement: [Köpenick, hasBodyOfWater, Müggelsee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Müggelsee Context triple: [Köpenick, hasBodyOfWater, Müggelsee]
-
A.
Müggelsee
chosen
Müggelsee is the largest lake in Berlin, Germany, known for its popular recreational areas and natural surroundings.
-
B.
Starnberger See
Starnberger See is a large, scenic lake in southern Germany known for its affluent lakeside communities, recreational activities, and historical associations with Bavarian royalty.
-
C.
Griebnitzsee
Griebnitzsee is a lake on the southwestern outskirts of Berlin, Germany, known for its scenic waterfront, historic villas, and role as part of the former inner German border.
-
D.
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.
-
E.
Grunewaldsee
Grunewaldsee is a popular forest lake in Berlin known for its scenic surroundings and dog-friendly bathing areas.
- 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_69c688796c148190adb2f1596f595f22 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e458ad9c81908c3f492b317ce291 |
completed | March 27, 2026, 8:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79c880dc08190813bd9bac580530a |
completed | March 28, 2026, 9:16 a.m. |
Created at: March 27, 2026, 2:38 p.m.