Upload old_bailey_proceedings.py

old_bailey_proceedings.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 os
+import datasets
+import glob
+import xml.etree.ElementTree as ET
+
+_CITATION = """
+@misc{Old Bailey Proceedings,
+  author    = {Mariona Coll Ardanuy and
+               Federico Nanni and
+               Kaspar Beelen and
+               Kasra Hosseini and
+               Ruth Ahnert and
+               Jon Lawrence and
+               Katherine McDonough and
+               Giorgia Tolfo and
+               Daniel C. S. Wilson and
+               Barbara McGillivray},
+  title     = {Living Machines: {A} study of atypical animacy},
+  journal   = {CoRR},
+  volume    = {abs/2005.11140},
+  year      = {2020},
+  url       = {https://arxiv.org/abs/2005.11140},
+  eprinttype = {arXiv},
+  eprint    = {2005.11140},
+  timestamp = {Sat, 23 Jan 2021 01:12:25 +0100},
+  biburl    = {https://dblp.org/rec/journals/corr/abs-2005-11140.bib},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
+}
+"""
+
+
+_DESCRIPTION = """The dataset consists of 2,163 transcriptions of the Proceedings and 475 Ordinary's Accounts marked up in TEI-XML, 
+and contains some documentation covering the data structure and variables. Each Proceedings file represents one session of the court (1674-1913), 
+and each Ordinary's Account file represents a single pamphlet (1676-1772)
+"""
+
+_HOMEPAGE = "https://www.dhi.ac.uk/projects/old-bailey/"
+
+_DATASETNAME = "old_bailey_proceedings"
+
+_LICENSE = "Creative Commons Attribution 4.0 International"
+
+_URLS = {
+    _DATASETNAME: "https://www.dhi.ac.uk/san/data/oldbailey/oldbailey.zip",
+}
+
+logger = datasets.utils.logging.get_logger(__name__)
+
+
+class OldBaileyProceedings(datasets.GeneratorBasedBuilder):
+    """The dataset consists of 2,163 transcriptions of the Proceedings and 475 Ordinary's Accounts marked up in TEI-XML,
+    and contains some documentation covering the data structure and variables. Each Proceedings file represents one session of the court (1674-1913),
+     and each Ordinary's Account file represents a single pamphlet (1676-1772)"""
+
+    VERSION = datasets.Version("7.2.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "id": datasets.Value("string"),
+                "text": datasets.Value("string"),
+                "places": datasets.Sequence(datasets.Value("string")),
+                "type": datasets.Value("string"),
+                "persons": datasets.Sequence(datasets.Value("string")),
+                "date": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = _URLS[_DATASETNAME]
+        data_dir = dl_manager.download_and_extract(urls)
+        oa_dir = "ordinarysAccounts"
+        obp_dir = "sessionsPapers"
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data_dirs": {
+                        "OA": os.path.join(data_dir, oa_dir),
+                        "OBP": os.path.join(data_dir, obp_dir),
+                    },
+                },
+            ),
+        ]
+
+    def convert_text_to_features(self, file, key):
+        if key == "OA":
+            root_tag = "p"
+        else:
+            root_tag = "div1/p"
+        try:
+            xml_data = ET.parse(file)
+            root = xml_data.getroot()
+            start = root.find("./text/body/div0")
+            id = start.attrib["id"]
+            date = start.find("interp[@type='date']").attrib["value"]
+            text_parts = []
+            places, persons = [], []
+            for content in start.findall(root_tag):
+                for place in content.findall("placeName"):
+                    if place.text:
+                        place_name = place.text.replace("\n", "").strip()
+                    if place_name:
+                        places.append(place.text)
+                for person in content.findall("persName"):
+                    full_name = []
+                    for name_part in person.itertext():
+                        name_part = (
+                            name_part.replace("\n", "").replace("\t", "").strip()
+                        )
+                        if name_part:
+                            full_name.append(name_part)
+                    if full_name:
+                        persons.append(" ".join(full_name))
+                for text_snippet in content.itertext():
+                    text_snippet = (
+                        text_snippet.replace("\n", "").replace("\t", "").strip()
+                    )
+                    if text_snippet:
+                        text_parts.append(text_snippet)
+            full_text = " ".join(text_parts)
+            return 0, {
+                "id": id,
+                "date": date,
+                "type": key,
+                "places": places,
+                "persons": persons,
+                "text": full_text,
+            }
+        except Exception as e:
+            return -1, repr(e)
+
+    def _generate_examples(self, data_dirs):
+        for key, data_dir in data_dirs.items():
+            for file in glob.glob(os.path.join(data_dir, "*.xml")):
+                status_code, ret_val = self.convert_text_to_features(file, key)
+                if status_code:
+                    logger.warn(f"{file}:{ret_val}")
+                    input()
+                    continue
+                else:
+                    yield ret_val["id"], ret_val