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---
license: mit
language:
- de
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
task_categories:
- question-answering
pretty_name: 'LHM Dienstleistungen: QA'
size_categories:
- 1K<n<10K
---
# 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 |