language:
- sv
license: cc-by-4.0
size_categories:
- 1M<n<10M
pretty_name: Open Riksdag-103
tags:
- diachronic
- semantic change
dataset_info:
- config_name: sentences
features:
- name: sentence
dtype: string
- name: doc_type
dtype: string
- name: doc_id
dtype: string
- name: date
dtype: timestamp[s]
splits:
- name: train
num_bytes: 8436701719
num_examples: 56846721
download_size: 1516962051
dataset_size: 8436701719
- config_name: target-103
features:
- name: sentence
dtype: string
- name: doc_type
dtype: string
- name: doc_id
dtype: string
- name: date
dtype: timestamp[s]
- name: lemma
dtype: string
- name: start
dtype: int32
- name: end
dtype: int32
- name: pos
dtype: string
splits:
- name: train
num_bytes: 8138875561
num_examples: 33393155
download_size: 1434826241
dataset_size: 8138875561
This is a dataset of text from the Riksdag, Sweden's national legislative body.
The original data is availble without a license under the Re-use of Public Administration Documents Act (2010:566) at https://data.riksdagen.se/data/dokument
This dataset is derivative of a version compiled by Språkbanken Text (SBX) at the University of Gothenburg (Sweden). That version consists of XML files split by source document type (motions, questions, protocol, etc.) and includes additional linguistic annotations. It is available under a CC BY 4.0 license at https://spraakbanken.gu.se/resurser/rd
The focus of this huggingface dataset is to organise the data for fine-grained diachronic modeling. In a nutshell, this version offers:
- all sentences including one or more of 103 target words, which were chosen by TF-IDF (described below)
- per-month subsets (with all document types combined)
- one line per sentence (sentences shorter than 4 words were discarded)
- data includes: date, document_type, document_id, target_word, and text.
The dataset builder requires a years argument, which must be an interable of years between 1979 and 2019 (inclusive). This can be supplied to the load_dataset function as a keyword argument.
For example, to load raw sentences from the prop and bet data sources run:
from datasets import load_dataset
data = load_dataset('ChangeIsKey/open-riksdag', 'sentences' years=range(1999,2000), sources=['prop', 'bet'])
License is CC BY 4.0 with attribution.