Triple
T9010328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landkreis Günzburg |
E215451
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Waldstetten (Günzburg)
Waldstetten (Günzburg) is a small municipality in the district of Günzburg in the Bavarian region of Swabia, Germany.
|
E772656
|
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: Waldstetten (Günzburg) | Statement: [Landkreis Günzburg, contains, Waldstetten (Günzburg)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waldstetten (Günzburg) Context triple: [Landkreis Günzburg, contains, Waldstetten (Günzburg)]
-
A.
Vaterstetten
Vaterstetten is a municipality in the district of Ebersberg near Munich in Bavaria, Germany, known as a residential suburb with strong transport links to the Bavarian capital.
-
B.
Wolfratshausen
Wolfratshausen is a Bavarian town in southern Germany known for its historic old town, riverside setting on the Loisach and Isar, and proximity to Munich and the Alps.
-
C.
Eggenfelden
Eggenfelden is a town in southeastern Germany known as a local commercial and cultural center within the region of Lower Bavaria.
-
D.
Stetten
Stetten is a locality within the town of Lichtenfels in the German state of Bavaria.
-
E.
Oberwallenstadt
Oberwallenstadt is a village and district of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
- 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: Waldstetten (Günzburg) Triple: [Landkreis Günzburg, contains, Waldstetten (Günzburg)]
Generated description
Waldstetten (Günzburg) is a small municipality in the district of Günzburg in the Bavarian region of Swabia, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Waldstetten (Günzburg) Target entity description: Waldstetten (Günzburg) is a small municipality in the district of Günzburg in the Bavarian region of Swabia, Germany.
-
A.
Vaterstetten
Vaterstetten is a municipality in the district of Ebersberg near Munich in Bavaria, Germany, known as a residential suburb with strong transport links to the Bavarian capital.
-
B.
Wolfratshausen
Wolfratshausen is a Bavarian town in southern Germany known for its historic old town, riverside setting on the Loisach and Isar, and proximity to Munich and the Alps.
-
C.
Eggenfelden
Eggenfelden is a town in southeastern Germany known as a local commercial and cultural center within the region of Lower Bavaria.
-
D.
Stetten
Stetten is a locality within the town of Lichtenfels in the German state of Bavaria.
-
E.
Oberwallenstadt
Oberwallenstadt is a village and district of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
- 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_69ca83a2bf088190986ee7a8eb90407d |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc69c00ae8819090786385a72e8baf |
completed | April 1, 2026, 12:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfdb9dca848190952427bb5712081f |
completed | April 3, 2026, 3:24 p.m. |
| NEDg | Description generation | batch_69cfdc5b230881908057cc868e44ea44 |
completed | April 3, 2026, 3:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfdcfc28288190b849b3f0216a7e9a |
completed | April 3, 2026, 3:30 p.m. |
Created at: March 30, 2026, 7:06 p.m.