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parlaMintSI.py

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+
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import csv
+import json
+import os
+
+import datasets
+
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {A great new dataset},
+author={huggingface, Inc.
+},
+year={2020}
+}
+"""
+
+_DESCRIPTION = """\
+ParlaMint 3.0 is a multilingual set of 26 comparable corpora containing parliamentary debates mostly starting in 2015 and extending to mid-2022.
+
+The corpora have extensive metadata, including aspects of the parliament; the speakers (name, gender, MP status, party affiliation, party coalition/opposition);
+are structured into time-stamped terms, sessions and meetings; and with speeches being marked by the speaker and their role (e.g. chair, regular speaker).
+The speeches also contain marked-up transcriber comments, such as gaps in the transcription, interruptions, applause, etc.
+Note that some corpora have further information, e.g. the year of birth of the speakers, links to their Wikipedia articles, their membership in various committees, etc.
+The corpora are also marked to the subcorpus they belong to ("reference", until 2020-01-30, "covid", from 2020-01-31, and "war", from 2022-02-24).
+
+The corpora are encoded according to the Parla-CLARIN TEI recommendation (https://clarin-eric.github.io/parla-clarin/), but have been encoded against the compatible,
+but much stricter ParlaMint encoding guidelines (https://clarin-eric.github.io/ParlaMint/) and schemas (included in this distribution.
+
+This entry contains the ParlaMint TEI-encoded corpora with the derived plain text versions of the corpora along with TSV metadata of the speeches.
+Also included is the 3.0 release of the data and scripts available at the GitHub repository of the ParlaMint project.
+
+This dataset contains only Slovenian parliamentary debates.
+"""
+
+_HOMEPAGE = "http://hdl.handle.net/11356/1486"
+
+_LICENSE = "Creative Commons - Attribution 4.0 International (CC BY 4.0)"
+
+_URLS = {
+    "parlamint": "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1486/ParlaMint-SI.tgz?sequence=24&isAllowed=y",
+}
+
+
+class ParlaMintSI(datasets.GeneratorBasedBuilder):
+    """This dataset contains transcriptions of Slovenian parliamentary debates and relevant metadata."""
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "ID": datasets.Value("string"),
+                "Title": datasets.Value("string"),
+                "Date": datasets.Value("string"),
+                "Body": datasets.Value("string"),
+                "Term": datasets.Value("string"),
+                "Session": datasets.Value("string"),
+                "Meeting": datasets.Value("int32"),
+                "Sitting": datasets.Value("string"),
+                "Agenda": datasets.Value("string"),
+                "Subcorpus": datasets.Value("string"),
+                "Speaker_role": datasets.Value("string"),
+                "Speaker_MP": datasets.Value("string"),
+                "Speaker_Minister": datasets.Value("string"),
+                "Speaker_party": datasets.Value("string"),
+                "Speaker_party_name": datasets.Value("string"),
+                "Party_status": datasets.Value("string"),
+                "Speaker_name": datasets.Value("string"),
+                "Speaker_gender": datasets.Value("string"),
+                "Speaker_birth": datasets.Value("string"),
+                "text": datasets.Value("string")
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = _URLS["parlamint"]
+        download_path = dl_manager.download_and_extract(urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": download_path,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        filepath = os.path.join(filepath, "ParlaMint-SI.txt")
+
+        for year_dir in os.listdir(filepath):
+            year_path = os.path.join(filepath, year_dir)
+            if os.path.isdir(year_path):
+                tsv_files = [f for f in os.listdir(year_path) if f.endswith(".tsv")]
+                for tsv_file in tsv_files:
+                    tsv_path = os.path.join(year_path, tsv_file)
+                    txt_path = os.path.join(year_path, tsv_file.replace("-meta.tsv", ".txt"))
+
+                    with open(tsv_path, "r", encoding="utf-8") as tsv, open(txt_path, "r", encoding="utf-8") as txt:
+                        tsv_reader = csv.DictReader(tsv, delimiter="\t")
+                        txt_content = txt.readlines()
+
+                        for row in tsv_reader:
+                            id_ = row.get("ID", "")
+                            text = next((line.split("\t")[1] for line in txt_content if line.startswith(id_)), "")
+                            example = {key: row.get(key, "") for key in row}
+                            example["text"] = text
+                            yield id_, example