# LHM-Dienstleistungen-QA - german public domain question-answering dataset 
Datasets created based on data from Munich city administration.
Format inspired by GermanQuAD. 
  
## Annotated by: 
-       Institute for Applied Artificial Intelligence: Leon Marius Schröder 
-       BettercallPaul GmbH: Clemens Gutknecht, Oubada Alkiddeh, Susanne Weiß 
-       Stadt München: Leon Lukas 
  
  
  
## Data basis 
Texts taken from the “Dienstleistungsfinder“ of the city of Munich administration. 
There information about services offered by city is presented online.
Information ranges from applying for an ID card to dispose of garbage.
- https://stadt.muenchen.de/service/ (Date 11/2022)
  
## Dataset statistics 
-       Shortest Question: 13 Characters 
-       Average Question: 68 Characters 
-       Longest Question: 183 Characters 
  
### Distribution of first sentence beginnings 
![all_words](alle.jpg " All sentence beginnings ") 
### Distribution of first sentence beginnings: Wie 
![Wie](Wie.jpg " Wie sentence beginnings") 
### Distribution of first sentence beginnings: Wo 
![Wo](wo.jpg " Wo sentence beginnings") 
### Distribution of first sentence beginnings: Was 
![Was](Was.jpg " Was sentence beginnings")

## Models trained using this datset
### QA
- cgutknecht/gelectra_large_gsqd-gq-LHM
### DPR 
- schreon/xnext-lhm_queries_encoder
- schreon/xnext-lhm_passages_encoder
task_categories:question-answering size_categories:1K<n<10K language:de license:mit QA region:us
{"language": ["de"], "license": "mit", "size_categories": ["1K<n<10K"], "task_categories": ["question-answering"], "pretty_name": "LHM Dienstleistungen: QA", "tags": ["QA"], "dataset_info": {"features": [{"name": "id", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "context", "dtype": "string"}, {"name": "question", "dtype": "string"}, {"name": "answers", "struct": [{"name": "answer_start", "sequence": "int64"}, {"name": "text", "sequence": "string"}]}], "splits": [{"name": "test", "num_bytes": 560403, "num_examples": 357}, {"name": "train", "num_bytes": 2826731, "num_examples": 1773}], "download_size": 710027, "dataset_size": 3387134}}
TAGS
#task_categories-question-answering #size_categories-1K<n<10K #language-German #license-mit #QA #region-us 

# LHM-Dienstleistungen-QA - german public domain question-answering dataset 
Datasets created based on data from Munich city administration.
Format inspired by GermanQuAD. 
  
## Annotated by: 
-       Institute for Applied Artificial Intelligence: Leon Marius Schröder 
-       BettercallPaul GmbH: Clemens Gutknecht, Oubada Alkiddeh, Susanne Weiß 
-       Stadt München: Leon Lukas 
  
  
  
## Data basis 
Texts taken from the “Dienstleistungsfinder“ of the city of Munich administration. 
There information about services offered by city is presented online.
Information ranges from applying for an ID card to dispose of garbage.
- URL (Date 11/2022)
  
## Dataset statistics 
-       Shortest Question: 13 Characters 
-       Average Question: 68 Characters 
-       Longest Question: 183 Characters 
  
### Distribution of first sentence beginnings 
!all_words 
### Distribution of first sentence beginnings: Wie 
!Wie 
### Distribution of first sentence beginnings: Wo 
!Wo 
### Distribution of first sentence beginnings: Was 
!Was

## Models trained using this datset
### QA
- cgutknecht/gelectra_large_gsqd-gq-LHM
### DPR 
- schreon/xnext-lhm_queries_encoder
- schreon/xnext-lhm_passages_encoder
# LHM-Dienstleistungen-QA - german public domain question-answering dataset 
Datasets created based on data from Munich city administration.
Format inspired by GermanQuAD. ## Annotated by: 
-       Institute for Applied Artificial Intelligence: Leon Marius Schröder 
-       BettercallPaul GmbH: Clemens Gutknecht, Oubada Alkiddeh, Susanne Weiß 
-       Stadt München: Leon Lukas ## Data basis 
Texts taken from the “Dienstleistungsfinder“ of the city of Munich administration. 
There information about services offered by city is presented online.
Information ranges from applying for an ID card to dispose of garbage.
- URL (Date 11/2022) ## Dataset statistics 
-       Shortest Question: 13 Characters 
-       Average Question: 68 Characters 
-       Longest Question: 183 Characters ### Distribution of first sentence beginnings 
!all_words ### Distribution of first sentence beginnings: Wie 
!Wie ### Distribution of first sentence beginnings: Wo 
!Wo ### Distribution of first sentence beginnings: Was 
!Was ## Models trained using this datset ### QA
- cgutknecht/gelectra_large_gsqd-gq-LHM ### DPR 
- schreon/xnext-lhm_queries_encoder
- schreon/xnext-lhm_passages_encoder
TAGS
#task_categories-question-answering #size_categories-1K<n<10K #language-German #license-mit #QA #region-us 
 # LHM-Dienstleistungen-QA - german public domain question-answering dataset 
Datasets created based on data from Munich city administration.
Format inspired by GermanQuAD. ## Annotated by: 
-       Institute for Applied Artificial Intelligence: Leon Marius Schröder 
-       BettercallPaul GmbH: Clemens Gutknecht, Oubada Alkiddeh, Susanne Weiß 
-       Stadt München: Leon Lukas ## Data basis 
Texts taken from the “Dienstleistungsfinder“ of the city of Munich administration. 
There information about services offered by city is presented online.
Information ranges from applying for an ID card to dispose of garbage.
- URL (Date 11/2022) ## Dataset statistics 
-       Shortest Question: 13 Characters 
-       Average Question: 68 Characters 
-       Longest Question: 183 Characters ### Distribution of first sentence beginnings 
!all_words ### Distribution of first sentence beginnings: Wie 
!Wie ### Distribution of first sentence beginnings: Wo 
!Wo ### Distribution of first sentence beginnings: Was 
!Was ## Models trained using this datset ### QA
- cgutknecht/gelectra_large_gsqd-gq-LHM ### DPR 
- schreon/xnext-lhm_queries_encoder
- schreon/xnext-lhm_passages_encoder
passage: TAGS
#task_categories-question-answering #size_categories-1K<n<10K #language-German #license-mit #QA #region-us 
# LHM-Dienstleistungen-QA - german public domain question-answering dataset 
Datasets created based on data from Munich city administration.
Format inspired by GermanQuAD.## Annotated by: 
-       Institute for Applied Artificial Intelligence: Leon Marius Schröder 
-       BettercallPaul GmbH: Clemens Gutknecht, Oubada Alkiddeh, Susanne Weiß 
-       Stadt München: Leon Lukas## Data basis 
Texts taken from the “Dienstleistungsfinder“ of the city of Munich administration. 
There information about services offered by city is presented online.
Information ranges from applying for an ID card to dispose of garbage.
- URL (Date 11/2022)## Dataset statistics 
-       Shortest Question: 13 Characters 
-       Average Question: 68 Characters 
-       Longest Question: 183 Characters### Distribution of first sentence beginnings 
!all_words### Distribution of first sentence beginnings: Wie 
!Wie### Distribution of first sentence beginnings: Wo 
!Wo### Distribution of first sentence beginnings: Was 
!Was## Models trained using this datset### QA
- cgutknecht/gelectra_large_gsqd-gq-LHM### DPR 
- schreon/xnext-lhm_queries_encoder
- schreon/xnext-lhm_passages_encoder