Triple
T5252099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunzenhausen |
E118611
|
entity |
| Predicate | hasNearbyLake |
P17985
|
FINISHED |
| Object |
Altmühlsee
Altmühlsee is an artificial recreational lake in Bavaria, Germany, popular for swimming, sailing, and nature conservation.
|
E509447
|
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: Altmühlsee | Statement: [Gunzenhausen, hasNearbyLake, Altmühlsee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altmühlsee Context triple: [Gunzenhausen, hasNearbyLake, Altmühlsee]
-
A.
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.
-
B.
Ammersee
Ammersee is a large glacial lake in southern Germany known for its scenic shores, recreational activities, and proximity to the Alps.
-
C.
Chiemsee
Chiemsee is one of Germany’s largest lakes, famed for its scenic Alpine setting and historic islands such as Herrenchiemsee with its royal palace.
-
D.
Schluchsee
Schluchsee is a large reservoir and popular recreational lake in Germany’s Black Forest, known for swimming, sailing, and scenic hiking.
-
E.
Oberaarsee
Oberaarsee is a high-altitude reservoir lake in the Swiss Alps, known for its striking turquoise waters and surrounding glacier-fed mountain scenery.
- 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: Altmühlsee Triple: [Gunzenhausen, hasNearbyLake, Altmühlsee]
Generated description
Altmühlsee is an artificial recreational lake in Bavaria, Germany, popular for swimming, sailing, and nature conservation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Altmühlsee Target entity description: Altmühlsee is an artificial recreational lake in Bavaria, Germany, popular for swimming, sailing, and nature conservation.
-
A.
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.
-
B.
Ammersee
Ammersee is a large glacial lake in southern Germany known for its scenic shores, recreational activities, and proximity to the Alps.
-
C.
Chiemsee
Chiemsee is one of Germany’s largest lakes, famed for its scenic Alpine setting and historic islands such as Herrenchiemsee with its royal palace.
-
D.
Schluchsee
Schluchsee is a large reservoir and popular recreational lake in Germany’s Black Forest, known for swimming, sailing, and scenic hiking.
-
E.
Oberaarsee
Oberaarsee is a high-altitude reservoir lake in the Swiss Alps, known for its striking turquoise waters and surrounding glacier-fed mountain scenery.
- 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_69bd446978108190bb5f9c5c23d93f88 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b7b840881908bb1ecb8a0047382 |
completed | March 20, 2026, 4:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf10cdb614819092621690e836338e |
completed | March 21, 2026, 9:42 p.m. |
| NEDg | Description generation | batch_69bf11949c8c8190ad3643d1accdf8a4 |
completed | March 21, 2026, 9:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf11f901e08190b1d708ed88ea7865 |
completed | March 21, 2026, 9:47 p.m. |
Created at: March 20, 2026, 1:50 p.m.