Triple
T6848245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Müggelsee |
E157949
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Großer 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: Großer Müggelsee | Statement: [Müggelsee, hasPart, Großer Müggelsee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Großer Müggelsee Context triple: [Müggelsee, hasPart, Großer Müggelsee]
-
A.
Tegeler See
Tegeler See is a large lake in the Tegel district of Berlin, Germany, popular for recreation, boating, and its surrounding natural areas.
-
B.
Müggelsee
chosen
Müggelsee is the largest lake in Berlin, Germany, known for its popular recreational areas and natural surroundings.
-
C.
Schlachtensee
Schlachtensee is a lake and popular recreational area in southwestern Berlin, known for swimming, walking trails, and its surrounding forested landscape.
-
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.
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.
- 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_69c6882ed4c081909dc465a7cf8838be |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d7ce3e7481908e0472b8faafa473 |
completed | March 27, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748b5a7c08190983bd355a1bc76d7 |
completed | March 28, 2026, 3:19 a.m. |
Created at: March 27, 2026, 2:20 p.m.