Triple
T17816480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grunewaldsee |
E444856
|
entity |
| Predicate | nearby |
P350
|
FINISHED |
| Object |
Hundekehlesee
Hundekehlesee is a small lake in Berlin’s Grunewald forest, popular for recreation and nature walks.
|
E1290160
|
NE FINISHED |
How this triple was built (4 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: Hundekehlesee | Statement: [Grunewaldsee, nearby, Hundekehlesee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hundekehlesee Context triple: [Grunewaldsee, nearby, Hundekehlesee]
-
A.
Stadtsee
Stadtsee is a small lake located in the town of Bad Waldsee in southern Germany, known for its scenic setting and recreational use.
-
B.
Muldestausee
Muldestausee is a municipality in the district of Anhalt-Bitterfeld in Saxony-Anhalt, Germany, known for the large Mulde reservoir and its surrounding natural and recreational areas.
-
C.
Tachinger See
Tachinger See is a small scenic lake in the Chiemgau region of Bavaria, Germany, known for swimming, fishing, and its tranquil natural surroundings.
-
D.
Glindower See
Glindower See is a natural lake in the Potsdam-Mittelmark district of Brandenburg, Germany, known for its scenic surroundings and recreational opportunities.
-
E.
Schwansee
Schwansee is a picturesque alpine lake in Bavaria, Germany, known for its scenic setting near Neuschwanstein and Hohenschwangau castles.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hundekehlesee Triple: [Grunewaldsee, nearby, Hundekehlesee]
Generated description
Hundekehlesee is a small lake in Berlin’s Grunewald forest, popular for recreation and nature walks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hundekehlesee Target entity description: Hundekehlesee is a small lake in Berlin’s Grunewald forest, popular for recreation and nature walks.
-
A.
Stadtsee
Stadtsee is a small lake located in the town of Bad Waldsee in southern Germany, known for its scenic setting and recreational use.
-
B.
Muldestausee
Muldestausee is a municipality in the district of Anhalt-Bitterfeld in Saxony-Anhalt, Germany, known for the large Mulde reservoir and its surrounding natural and recreational areas.
-
C.
Tachinger See
Tachinger See is a small scenic lake in the Chiemgau region of Bavaria, Germany, known for swimming, fishing, and its tranquil natural surroundings.
-
D.
Glindower See
Glindower See is a natural lake in the Potsdam-Mittelmark district of Brandenburg, Germany, known for its scenic surroundings and recreational opportunities.
-
E.
Schwansee
Schwansee is a picturesque alpine lake in Bavaria, Germany, known for its scenic setting near Neuschwanstein and Hohenschwangau castles.
- F. None of above. chosen
Provenance (5 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4887f7d048190b6d813b9f0fab3e7 |
completed | April 19, 2026, 7:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02ff643ca08190a427b7cabfd91dab |
completed | May 12, 2026, 10:22 a.m. |
| NEDg | Description generation | batch_6a0303b3b4c881908960293a5985d8c7 |
completed | May 12, 2026, 10:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a030408cebc8190835c005a5f380793 |
completed | May 12, 2026, 10:42 a.m. |
Created at: April 10, 2026, 10:14 a.m.