first version innit

data_sources.txt

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+bet ds eun flista fpm frsrdg ip kammakt kom mot ovr prop prot rskr samtr skfr sou tlista utr utsk yttr 

open-riksdag.py

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+# Config file by Bill Noble, adapted from the Kubhist 2 dataset by Simon Hengchen, https://hengchen.net
+
+import os
+import datasets
+import json
+from datasets.data_files import DataFilesDict
+from pathlib import Path
+
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = """
+This is a dataset of text from the Riksdag, Sweden's 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 document source (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. To that end, this dataset includes two configurations:
+
+# Configurations
+
+## `sentences`
+
+This configuration provides sentences in raw text format with their original whitespace. Sentence-level tokenisation was performed by Språkbanken. 
+
+`datasets.load_dataset('ChangeIsKey/open-riksdag', 'sentences', years=YEARS, sources=SOURCES)`
+
+- `YEARS:list(int)` - years in the range [1960, 2022] from which sentences are drawn
+- `SOURCES:list(str)` - the Open Riksdag data is split into different data sources
+    - `bet` _Betänkande_ ~ reports
+    - `ds` 
+    - `eun` _EUN_ ~ documents from the EU committee
+    - `flista` _Föredragningslistor_ ~ Lists of speeches
+    - `fpm` _faktapromemorior_  ~ factual memoranda on EU commission proposals 
+    - `frsrdg` _Framställning/redogörelse_ ~ petitions and reports from bodies appointed by the Riksdag
+    ...
+
+data fields
+
+- `sentence` - 
+- `date` - 
+- `source`
+- `document_id`
+...
+
+
+## `targets-103`
+
+- `target_lemma`
+- `start`
+- `end`
+
+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, source, document_id, target_word, and text.
+
+License is CC BY 4.0 with attribution.
+"""
+
+_CONFIGS = ['sentences', 'target-103']
+_ALL_YEARS = list(range(1979, 2020))
+with open("data_sources.txt") as f:
+    _ALL_SOURCES = f.read().strip().split(' ')
+with open("target_terms.txt") as f:
+    _ALL_TARGET_TERMS = f.read().strip().split(' ')
+_TERM_TO_ID = {t: i for i,t in enumerate(_ALL_TARGET_TERMS)}
+
+class OpenRiksdagConfig(datasets.BuilderConfig):
+    """BuilderConfig for openRD-103."""
+
+    def __init__(self, name='sentences', years=_ALL_YEARS, sources=_ALL_SOURCES, targets=_ALL_TARGET_TERMS, **kwargs):
+        """Constructs an open-riksdag dataset.
+        Args:
+        year: integer year between 1979 and 2019
+        **kwargs: keyword arguments forwarded to super.
+        """
+
+        if not all(year in _ALL_YEARS for year in years):
+            raise ValueError("`years` should contain integers between 1979 and 2019")
+        self.years = list(set(years))
+
+        if not all(year in _ALL_YEARS for year in years):
+            raise ValueError(f"`sources` should be a subset of {_ALL_SOURCES}")
+        self.sources = list(set(sources))
+
+        try:
+            if targets and isinstance(targets[0], str):
+                targets = [_TERM_TO_ID[t] for t in targets]
+            assert all(t in _TERM_TO_ID.values() for t in targets)
+            targets = list(set(targets))
+        except (KeyError, AssertionError) as e:
+            print(e)
+            raise ValueError(f"`targets` should be a subset of {_ALL_TARGET_TERMS} or integer indexes there of")
+        self.targets = list(set(targets))
+    
+        super().__init__(
+            name = name,
+            version = datasets.Version("1.1.0", ""),
+            data_dir = kwargs.get('data_dir', "./data") ,
+            **kwargs
+        )
+
+class OpenRiksdag(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIG_CLASS = OpenRiksdagConfig
+
+    BUILDER_CONFIGS = [
+        OpenRiksdagConfig(
+            name='sentences',
+            description="Raws sentences from Riksdagens öppnadata",
+        ),
+        OpenRiksdagConfig(
+            name='target-103',
+            description="Sentences from Riksdagens öppna data with a selection of 103 target words"
+        )
+    ]
+
+    def _info(self):
+
+        features = {
+            "sentence": datasets.Value("string"), 
+            "doc_type": datasets.Value("string"), 
+            "doc_id": datasets.Value("string"), 
+            "date": datasets.Value("timestamp[s]")
+         }
+
+        if self.config.name == 'target-103':
+            target_features = {
+                "lemma": datasets.Value("string"), 
+                "start": datasets.Value("int32"), 
+                "end": datasets.Value("int32"), 
+                "pos": datasets.Value("string")
+            }
+            features = {**features, **target_features}
+
+        return datasets.DatasetInfo(
+            features = datasets.Features(features),
+            supervised_keys=None,
+            homepage="https://github.com/ChangeIsKey",
+        )
+
+    def _split_generators(self, dl_manager):
+
+        data_dir = Path(self.config.data_dir)/self.config.name 
+        if self.config.name == 'sentences':
+            possible_files = [data_dir/f"{y}_{s}.jsonl.bz2" for y in self.config.years for s in self.config.sources]
+        elif self.config.name == 'target-103':
+            possible_files = [data_dir/f"{t:03d}/{y}_target{t:03d}_{s}.jsonl.bz2" for y in self.config.years 
+                                                                for t in self.config.targets for s in self.config.sources]
+        existing_files = list(data_dir.glob("*.jsonl.bz2"))
+        data_files = [f for f in possible_files if f in existing_files]
+        data_files = DataFilesDict({f"train": data_files})
+        extracted_paths = dl_manager.download_and_extract(data_files)
+        return [datasets.SplitGenerator(
+            name=datasets.Split.TRAIN, 
+            gen_kwargs={"filepaths": extracted_paths['train']}
+            )
+        ]
+
+    def _generate_examples(self, filepaths):
+        """Yields examples."""
+        key = 0
+        for filepath in filepaths:
+            with open(filepath, encoding='utf-8') as f:
+                for line in f:
+                    item = json.loads(line)
+                    yield key, item
+                    key+=1

target_terms.txt

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+% april arbetsförmedling arbetsgivare arbetslöshet arbetsmarknad arbetsmarknadsminister augusti barn betala bil bolag bostad brott december drabba ekonomisk elev februari finansminister flicka flygplats forskning fru företag försvarsmakt försvarsminister försäkringskassa förälder gammal grupp herr hälsa högskola internationell isolering januari jobb juli juni justitieminister kommun kommunal kostnad krona kultur kunskap kvinna lag lagstiftning landsbygd landsting lokal län lärare m maj man mars migrationsminister miljard miljon miljö miljöminister myndighet mänsklig mål nationell ni november näringsminister offentlig oktober organisation ovanstående person polis procent rapport regel region rättighet september sjukvård skatt socialminister stat statlig statsminister statsråd student stöd trafikverk ung ungdom utbildning utbildningsminister utredning utrikesminister verksamhet våld vård återtagen