Triple
T10988183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kitzingen (district) |
E259684
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Rüdenhausen
Rüdenhausen is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and Franconian cultural heritage.
|
E988570
|
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: Rüdenhausen | Statement: [Kitzingen (district), hasMunicipality, Rüdenhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rüdenhausen Context triple: [Kitzingen (district), hasMunicipality, Rüdenhausen]
-
A.
Nennhausen
Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
-
B.
Ochsenhausen
Ochsenhausen is a small historic town in the German state of Baden-Württemberg, best known for its former Benedictine monastery, Ochsenhausen Abbey.
-
C.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Thannhausen
Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
-
E.
Aidhausen
Aidhausen is a small municipality in the Lower 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: Rüdenhausen Triple: [Kitzingen (district), hasMunicipality, Rüdenhausen]
Generated description
Rüdenhausen is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and Franconian cultural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rüdenhausen Target entity description: Rüdenhausen is a small municipality in the Kitzingen district of Bavaria, Germany, known for its rural character and Franconian cultural heritage.
-
A.
Nennhausen
Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
-
B.
Ochsenhausen
Ochsenhausen is a small historic town in the German state of Baden-Württemberg, best known for its former Benedictine monastery, Ochsenhausen Abbey.
-
C.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Thannhausen
Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
-
E.
Aidhausen
Aidhausen is a small municipality in the Lower 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d787b574d08190adec34b814a26437 |
completed | April 9, 2026, 11:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6554d0b0081909cc031ff06b796c0 |
completed | May 2, 2026, 7:49 p.m. |
| NEDg | Description generation | batch_69f6566dccc0819085e059c7b0288f6c |
completed | May 2, 2026, 7:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f657aec8fc8190b3b08ccb95595958 |
completed | May 2, 2026, 7:59 p.m. |
Created at: April 8, 2026, 9:24 p.m.