Convert dataset to Parquet (#3)

- Convert dataset to Parquet (1d50d84c243faced4cdb6ef1560ca26f0cade44f)
- Delete loading script (1460b4208c645a630774ad60556a7ce684bceb13)
- Delete legacy dataset_infos.json (56eba7a9bf450cb97ce593f6696c58802252a672)

README.md

@@ -1,16 +1,15 @@
 ---
 annotations_creators:
 - expert-generated
-language:
-- en
 language_creators:
 - expert-generated
 - machine-generated
+language:
+- en
 license:
 - cc-by-4.0
 multilinguality:
 - monolingual
-pretty_name: Old Bailey Proceedings
 size_categories:
 - 1K<n<10K
 source_datasets:
@@ -22,6 +21,32 @@ task_ids:
 - multi-class-classification
 - language-modeling
 - masked-language-modeling
+pretty_name: Old Bailey Proceedings
+dataset_info:
+  features:
+  - name: id
+    dtype: string
+  - name: text
+    dtype: string
+  - name: places
+    sequence: string
+  - name: type
+    dtype: string
+  - name: persons
+    sequence: string
+  - name: date
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 719949847
+    num_examples: 2638
+  download_size: 370751172
+  dataset_size: 719949847
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
 ---
 [Needs More Information]
 

data/train-00000-of-00002.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:10051c5fe9d2ca4005de87f4ce61a5468bb2a1697fee7ddf63f86ad2fa63408f
+size 152740985

data/train-00001-of-00002.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e8ea3ddcfae256e00a6798a4f0837a23774645a93d42e0751c3f9c4b6126dd8d
+size 218010187

dataset_infos.json

@@ -1 +0,0 @@
-{"default": {"description": "The dataset consists of 2,163 transcriptions of the Proceedings and 475 Ordinary's Accounts marked up in TEI-XML, \nand contains some documentation covering the data structure and variables. Each Proceedings file represents one session of the court (1674-1913), \nand each Ordinary's Account file represents a single pamphlet (1676-1772)\n", "citation": "@article{Howard2017,\nauthor = \"Sharon Howard\",\ntitle = \"{Old Bailey Online XML Data}\",\nyear = \"2017\",\nmonth = \"4\",\nurl = \"https://figshare.shef.ac.uk/articles/dataset/Old_Bailey_Online_XML_Data/4775434\",\ndoi = \"10.15131/shef.data.4775434.v2\"\n}\n", "homepage": "https://www.dhi.ac.uk/projects/old-bailey/", "license": "Creative Commons Attribution 4.0 International", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "places": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "type": {"dtype": "string", "id": null, "_type": "Value"}, "persons": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "date": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "old_bailey_proceedings", "config_name": "default", "version": {"version_str": "7.2.0", "description": null, "major": 7, "minor": 2, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 719955987, "num_examples": 2638, "dataset_name": "old_bailey_proceedings"}}, "download_checksums": {"https://www.dhi.ac.uk/san/data/oldbailey/oldbailey.zip": {"num_bytes": 326259415, "checksum": "60d1e3b889089d0b47c933cf24b8db62838ab0fec793569bf516173a12622ca0"}}, "download_size": 326259415, "post_processing_size": null, "dataset_size": 719955987, "size_in_bytes": 1046215402}}

old_bailey_proceedings.py

@@ -1,149 +0,0 @@
-# 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 = """@article{Howard2017,
-author = "Sharon Howard",
-title = "{Old Bailey Online XML Data}",
-year = "2017",
-month = "4",
-url = "https://figshare.shef.ac.uk/articles/dataset/Old_Bailey_Online_XML_Data/4775434",
-doi = "10.15131/shef.data.4775434.v2"
-}
-"""
-
-
-_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"
-
-_URL = "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):
-        data_dir = dl_manager.download_and_extract(_URL)
-        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.exception(
-                        f"{os.path.basename(file)} could not be parsed properly"
-                    )
-                    continue
-                else:
-                    yield ret_val["id"], ret_val