Triple
T13530382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xanten |
E323116
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Kriemhildmühle
Kriemhildmühle is a historic windmill in the German town of Xanten, known as a prominent local landmark and tourist attraction.
|
E1045511
|
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: Kriemhildmühle | Statement: [Xanten, hasPart, Kriemhildmühle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kriemhildmühle Context triple: [Xanten, hasPart, Kriemhildmühle]
-
A.
Widdersberg
Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
-
B.
Pfaffnern
Pfaffnern is a small river in Switzerland that serves as a tributary of the Wigger.
-
C.
Ingoldingen
Ingoldingen is a small municipality in the German state of Baden-Württemberg, known for its rural character and location within the Upper Swabia region.
-
D.
Aumühle
Aumühle is a small municipality in northern Germany, known in part as the place where former German Grand Admiral and President Karl Dönitz died.
-
E.
Gundremmingen
Gundremmingen is a small Bavarian municipality best known for hosting one of Germany’s major nuclear power plants.
- 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: Kriemhildmühle Triple: [Xanten, hasPart, Kriemhildmühle]
Generated description
Kriemhildmühle is a historic windmill in the German town of Xanten, known as a prominent local landmark and tourist attraction.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kriemhildmühle Target entity description: Kriemhildmühle is a historic windmill in the German town of Xanten, known as a prominent local landmark and tourist attraction.
-
A.
Widdersberg
Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
-
B.
Pfaffnern
Pfaffnern is a small river in Switzerland that serves as a tributary of the Wigger.
-
C.
Ingoldingen
Ingoldingen is a small municipality in the German state of Baden-Württemberg, known for its rural character and location within the Upper Swabia region.
-
D.
Aumühle
Aumühle is a small municipality in northern Germany, known in part as the place where former German Grand Admiral and President Karl Dönitz died.
-
E.
Gundremmingen
Gundremmingen is a small Bavarian municipality best known for hosting one of Germany’s major nuclear power plants.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafba2c308190873efd15dfe26358 |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7549fc5f881908691eb62c1f5a5d5 |
completed | May 3, 2026, 1:58 p.m. |
| NEDg | Description generation | batch_69f7565846108190bb6550505af8ac5d |
completed | May 3, 2026, 2:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f75a2107e081909fd00af67938f2e9 |
completed | May 3, 2026, 2:22 p.m. |
Created at: April 9, 2026, 9:44 p.m.