Triple
T20206366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bodenseekreis |
E493361
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Daisendorf
Daisendorf is a small municipality in the Bodenseekreis district of Baden-Württemberg in southern Germany, near Lake Constance.
|
E1418565
|
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: Daisendorf | Statement: [Bodenseekreis, hasMunicipality, Daisendorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daisendorf Context triple: [Bodenseekreis, hasMunicipality, Daisendorf]
-
A.
Weisendorf
Weisendorf is a small municipality in the Erlangen-Höchstadt district of Bavaria, Germany, known for its rural character and proximity to the city of Erlangen.
-
B.
Neuendorf
Neuendorf is a small village on the Baltic Sea island of Hiddensee in Germany, known for its traditional thatched houses and maritime character.
-
C.
Diedorf
Diedorf is a market town in Bavaria, Germany, located just west of the city of Augsburg.
-
D.
Wilhelmsdorf
Wilhelmsdorf is a village-level subdivision of the town of Usingen in the Hochtaunus district of Hesse, Germany.
-
E.
Tasdorf
Tasdorf is a small municipality in northern Germany notable as the birthplace of the 19th-century opera composer Giacomo Meyerbeer.
- 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: Daisendorf Triple: [Bodenseekreis, hasMunicipality, Daisendorf]
Generated description
Daisendorf is a small municipality in the Bodenseekreis district of Baden-Württemberg in southern Germany, near Lake Constance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daisendorf Target entity description: Daisendorf is a small municipality in the Bodenseekreis district of Baden-Württemberg in southern Germany, near Lake Constance.
-
A.
Weisendorf
Weisendorf is a small municipality in the Erlangen-Höchstadt district of Bavaria, Germany, known for its rural character and proximity to the city of Erlangen.
-
B.
Neuendorf
Neuendorf is a small village on the Baltic Sea island of Hiddensee in Germany, known for its traditional thatched houses and maritime character.
-
C.
Diedorf
Diedorf is a market town in Bavaria, Germany, located just west of the city of Augsburg.
-
D.
Wilhelmsdorf
Wilhelmsdorf is a village-level subdivision of the town of Usingen in the Hochtaunus district of Hesse, Germany.
-
E.
Tasdorf
Tasdorf is a small municipality in northern Germany notable as the birthplace of the 19th-century opera composer Giacomo Meyerbeer.
- 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_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66d922ebc8190ae012da8ceba74dd |
completed | April 20, 2026, 6:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a084b805fdc819099b11150c8f4e62d |
completed | May 16, 2026, 10:48 a.m. |
| NEDg | Description generation | batch_6a084c041b5c8190881a6d08c4afe42f |
completed | May 16, 2026, 10:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a084c7dee808190a0883f7f0c7873a9 |
completed | May 16, 2026, 10:52 a.m. |
Created at: April 11, 2026, 11:38 p.m.