Add first version of Gigafida loader

ccGigafida.py

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+"""(A publicly available subsample of) a reference corpus of Slovene texts."""
+
+
+import glob
+import logging
+import os
+import os.path
+import re
+import xml.etree.ElementTree as ET
+from copy import deepcopy
+
+import datasets
+
+XML_NAMESPACE = "{http://www.w3.org/XML/1998/namespace}"
+
+
+def namespace(element):
+    # https://stackoverflow.com/a/12946675
+    m = re.match(r'\{.*\}', element.tag)
+    return m.group(0) if m else ''
+
+
+_CITATION = """\
+@misc{ccGigafida,
+    title = {Written corpus {ccGigafida} 1.0},
+    author = {Logar, Nata{\v s}a and Erjavec, Toma{\v z} and Krek, Simon and Gr{\v c}ar, Miha and Holozan, Peter},
+    url = {http://hdl.handle.net/11356/1035},
+    note = {Slovenian language resource repository {CLARIN}.{SI}},
+    copyright = {Creative Commons - Attribution-{NonCommercial}-{ShareAlike} 4.0 International ({CC} {BY}-{NC}-{SA} 4.0)},
+    issn = {2820-4042},
+    year = {2013}
+}
+"""
+
+_DESCRIPTION = """\
+The ccGigafida corpus contains a subsample of the Gigafida corpus. The Gigafida corpus is an extensive collection of 
+Slovene text of various genres, from daily newspapers, magazines, all kinds of books (fiction, non-fiction, textbooks), 
+web pages, transcriptions of parliamentary debates and similar.
+"""
+
+_HOMEPAGE = "http://eng.slovenscina.eu/korpusi/proste-zbirke"
+
+_LICENSE = "Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)"
+
+_URLS = {
+    "ccGigafida": "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1035/ccGigafidaV1_0.zip"
+}
+
+
+class CcGigafida(datasets.GeneratorBasedBuilder):
+    """(A publicly available subsample of) a reference corpus of Slovene texts."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "id_doc": datasets.Value("string"),
+                "doc_title": datasets.Value("string"),
+                "authors": datasets.Sequence(datasets.Value("string")),
+                "publish_date": datasets.Value("string"),
+                "publisher": datasets.Value("string"),
+                "genres": datasets.Sequence(datasets.Value("string")),
+                "doc_tokenized": datasets.Sequence(datasets.Sequence(datasets.Sequence(datasets.Value("string")))),
+                "doc_string": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
+                "id_sents": datasets.Sequence(datasets.Sequence(datasets.Value("string")))
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        # Allow user to specify path to the full Gigafida directory: `load_dataset(..., data_dir=...)`
+        if dl_manager.manual_dir is not None:
+            data_dir = dl_manager.manual_dir
+        else:
+            urls = _URLS["ccGigafida"]
+            data_dir = dl_manager.download_and_extract(urls)
+            data_dir = os.path.join(data_dir, "ccGigafidaV1_0")
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"data_dir": data_dir}
+            )
+        ]
+
+    def _generate_examples(self, data_dir):
+        GENRE_MAPPING = {
+            "SSJ.T": "tisk", "SSJ.T.K": "tisk/knjižno", "SSJ.T.K.L": "tisk/knjižno/leposlovno",
+            "SSJ.T.K.S": "tisk/knjižno/strokovno", "SSJ.T.P": "tisk/periodično", "SSJ.T.P.C": "tisk/periodično/časopis",
+            "SSJ.T.P.R": "tisk/periodično/revija", "SSJ.T.D": "tisk/drugo", "SSJ.I": "internet"
+        }
+        # genres are prefixed by "ssj:" in Gigafida 2.0
+        for genre, description in deepcopy(GENRE_MAPPING).items():
+            GENRE_MAPPING[f"ssj:{genre}"] = description
+
+        # Recursively search for xml files in subdirectories
+        all_files = [os.path.join(data_dir, file_name)
+                     for file_name in glob.glob(os.path.join(data_dir, "**", "*.xml"), recursive=True)
+                     if os.path.isfile(os.path.join(data_dir, file_name))]
+        all_files = sorted(all_files)  # fix order
+
+        for _idx_file, file_path in enumerate(all_files):
+            curr_doc = ET.parse(file_path)
+            root = curr_doc.getroot()
+            NAMESPACE = namespace(root)
+            id_doc = root.attrib[f"{XML_NAMESPACE}id"]
+
+            # Document metadata
+            bibl_el = root.find(f".//{NAMESPACE}bibl")
+            doc_title = bibl_el.find(f"{NAMESPACE}title").text.strip()
+            authors = list(map(lambda _tag: _tag.text.strip(), bibl_el.findall(f"{NAMESPACE}author")))
+            publish_date = bibl_el.find(f"{NAMESPACE}date").text.strip()
+            publisher = bibl_el.find(f"{NAMESPACE}publisher").text.strip()
+
+            category_tags = root.findall(f".//{NAMESPACE}catRef")
+            genres = []
+            for _tag in category_tags:
+                # in ccGigafida, the genres are noted with a "#" prefix
+                __tag = _tag.attrib["target"][1:] if _tag.attrib["target"].startswith("#") else _tag.attrib["target"]
+                mapped_tag = GENRE_MAPPING.get(__tag, None)
+                # In addition to the genre of the document, there is sometimes a category assigned by the deduplication tool (dedup:nodup)
+                if mapped_tag is None:
+                    continue
+
+                genres.append(mapped_tag)
+
+            # Tokenized and raw string version - raw string version preserves spaces
+            body_tag = root.find(f".//{NAMESPACE}body")
+            tokenized_doc, doc_str = [], []
+            doc_sent_ids = []
+
+            for para_tag in body_tag.findall(f".//{NAMESPACE}p"):
+                id_para = para_tag.attrib[f"{XML_NAMESPACE}id"]
+                tokenized_para, para_str = [], []
+                para_sent_ids = []
+
+                for _idx_sent, sent_tag in enumerate(para_tag.findall(f".//{NAMESPACE}s")):
+                    # ccGigafida does not have sentence IDs:
+                    #   construct ID by taking the paragraph ID + their index in the paragraph
+                    id_sent = sent_tag.attrib.get(f"{XML_NAMESPACE}id", None)
+                    if id_sent is None:
+                        id_sent = f"{id_para}.{_idx_sent}"
+
+                    tokenized_sent, str_sent = [], []
+                    for child_tag in sent_tag:
+                        tag_str = child_tag.tag[len(NAMESPACE):]
+                        if tag_str not in {"w", "S", "c", "pc"}:
+                            logging.warning(f"Found unexpected tag in a sentence: '{tag_str}', skipping it.")
+                            continue
+
+                        # Tag for whitespace in ccGigafida
+                        if tag_str == "S":
+                            str_sent.append(" ")
+
+                        # Tag for:
+                        # - single-letter characters in ccGigafida;
+                        # - whitespace in Gigafida
+                        elif tag_str == "c":
+                            str_sent.append(child_tag.text)
+                            if child_tag.text != " ":
+                                tokenized_sent.append(child_tag.text)
+
+                        # word or punctuation character
+                        else:
+                            str_sent.append(child_tag.text)
+                            tokenized_sent.append(child_tag.text)
+
+                    str_sent = "".join(str_sent)
+                    tokenized_para.append(tokenized_sent)
+                    para_str.append(str_sent)
+                    para_sent_ids.append(id_sent)
+
+                tokenized_doc.append(tokenized_para)
+                doc_str.append(para_str)
+                doc_sent_ids.append(para_sent_ids)
+
+            yield _idx_file, {
+                "id_doc": id_doc,
+                "doc_title": doc_title,
+                "authors": authors,
+                "publish_date": publish_date,
+                "publisher": publisher,
+                "genres": genres,
+                "doc_tokenized": tokenized_doc,
+                "doc_string": doc_str,
+                "id_sents": doc_sent_ids
+            }

dataset_infos.json

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+{"default": {"description": "The ccGigafida corpus contains a subsample of the Gigafida corpus. The Gigafida corpus is an extensive collection of \nSlovene text of various genres, from daily newspapers, magazines, all kinds of books (fiction, non-fiction, textbooks), \nweb pages, transcriptions of parliamentary debates and similar.\n", "citation": "@misc{ccGigafida,\n    title = {Written corpus {ccGigafida} 1.0},\n    author = {Logar, Nata{\u000b s}a and Erjavec, Toma{\u000b z} and Krek, Simon and Gr{\u000b c}ar, Miha and Holozan, Peter},\n    url = {http://hdl.handle.net/11356/1035},\n    note = {Slovenian language resource repository {CLARIN}.{SI}},\n    copyright = {Creative Commons - Attribution-{NonCommercial}-{ShareAlike} 4.0 International ({CC} {BY}-{NC}-{SA} 4.0)},\n    issn = {2820-4042},\n    year = {2013}\n}\n", "homepage": "http://eng.slovenscina.eu/korpusi/proste-zbirke", "license": "Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)", "features": {"id_doc": {"dtype": "string", "id": null, "_type": "Value"}, "doc_title": {"dtype": "string", "id": null, "_type": "Value"}, "authors": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "publish_date": {"dtype": "string", "id": null, "_type": "Value"}, "publisher": {"dtype": "string", "id": null, "_type": "Value"}, "genres": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "doc_tokenized": {"feature": {"feature": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "doc_string": {"feature": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "id_sents": {"feature": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "cc_gigafida", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2054478553, "num_examples": 31722, "dataset_name": "cc_gigafida"}}, "download_checksums": {"https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1035/ccGigafidaV1_0.zip": {"num_bytes": 954116273, "checksum": "448e284d6f92d54f123e2b7fa433c9d84d060f2db07c589e9b45a356a1f5242e"}}, "download_size": 954116273, "post_processing_size": null, "dataset_size": 2054478553, "size_in_bytes": 3008594826}}