Convert to parquet (loading scripts are no longer supported)

README.md

@@ -3,15 +3,14 @@ annotations_creators:
 - expert-generated
 - machine-generated
 language:
-- 'en'
+- en
 language_creators:
 - found
-paperswithcode_id: null
 license:
 - cc-by-sa-4.0
 multilinguality:
 - monolingual
-pretty_name: 'Corpus of Late Modern English Texts v3.1'
+pretty_name: Corpus of Late Modern English Texts v3.1
 size_categories:
 - n<1K
 source_datasets:
@@ -22,6 +21,183 @@ task_categories:
 task_ids:
 - multi-label-classification
 - masked-language-modeling
+dataset_info:
+- config_name: class
+  features:
+  - name: id
+    dtype: string
+  - name: period
+    dtype: string
+  - name: genre
+    dtype: string
+  - name: subgenre
+    dtype: string
+  - name: decade
+    dtype: string
+  - name: quarter_cent
+    dtype: string
+  - name: title
+    dtype: string
+  - name: notes
+    dtype: string
+  - name: comments
+    dtype: string
+  - name: author
+    dtype: string
+  - name: year
+    dtype: string
+  - name: text
+    list: string
+  - name: pos_tags
+    list:
+      class_label:
+        names:
+          '0': ADJ
+          '1': ADV
+          '2': ART
+          '3': CONJ
+          '4': INTJ
+          '5': PREP
+          '6': PRON
+          '7': PUNC
+          '8': SUBST
+          '9': SYM
+          '10': UNC
+          '11': VERB
+          '12': QUOT
+  splits:
+  - name: train
+    num_bytes: 641829326
+    num_examples: 333
+  download_size: 641860629
+  dataset_size: 641829326
+- config_name: plain
+  features:
+  - name: id
+    dtype: string
+  - name: period
+    dtype: string
+  - name: genre
+    dtype: string
+  - name: subgenre
+    dtype: string
+  - name: decade
+    dtype: string
+  - name: quarter_cent
+    dtype: string
+  - name: title
+    dtype: string
+  - name: notes
+    dtype: string
+  - name: comments
+    dtype: string
+  - name: author
+    dtype: string
+  - name: year
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 198791975
+    num_examples: 333
+  download_size: 115599939
+  dataset_size: 198791975
+- config_name: pos
+  features:
+  - name: id
+    dtype: string
+  - name: period
+    dtype: string
+  - name: genre
+    dtype: string
+  - name: subgenre
+    dtype: string
+  - name: decade
+    dtype: string
+  - name: quarter_cent
+    dtype: string
+  - name: title
+    dtype: string
+  - name: notes
+    dtype: string
+  - name: comments
+    dtype: string
+  - name: author
+    dtype: string
+  - name: year
+    dtype: string
+  - name: text
+    list: string
+  - name: pos_tags
+    list:
+      class_label:
+        names:
+          '0': CC
+          '1': CD
+          '2': DT
+          '3': EX
+          '4': FW
+          '5': IN
+          '6': JJ
+          '7': JJR
+          '8': JJS
+          '9': MD
+          '10': NN
+          '11': NNS
+          '12': NP
+          '13': NPS
+          '14': PDT
+          '15': POS
+          '16': PP
+          '17': PP$
+          '18': RB
+          '19': RBR
+          '20': RBS
+          '21': RP
+          '22': SENT
+          '23': SYM
+          '24': TO
+          '25': UH
+          '26': VB
+          '27': VBD
+          '28': VBG
+          '29': VBN
+          '30': VBZ
+          '31': VBP
+          '32': WDT
+          '33': WP
+          '34': WP$
+          '35': WRB
+          '36': XX0
+          '37': CURR
+          '38': PUN
+          '39': LQUO
+          '40': RQUO
+          '41': BRL
+          '42': BRR
+          '43': LS
+          '44': ':'
+          '45': $
+  splits:
+  - name: train
+    num_bytes: 641829326
+    num_examples: 333
+  download_size: 641861564
+  dataset_size: 641829326
+configs:
+- config_name: class
+  data_files:
+  - split: train
+    path: class/train-*
+- config_name: plain
+  data_files:
+  - split: train
+    path: plain/train-*
+- config_name: pos
+  data_files:
+  - split: train
+    path: pos/train-*
 ---
 # Dataset Card for clmet_3_1
 

class/train-00000-of-00002.parquet

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+size 268028629

clmet_3_1.py

@@ -1,292 +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.
-"""The Corpus of Late Modern English Texts, version 3.1 (CLMET3.1) has been created by Hendrik De Smet, 
-Susanne Flach, Hans-Jürgen Diller and Jukka Tyrkkö, as an offshoot of a bigger project developing a database
- of text descriptors (Diller, De Smet & Tyrkkö 2011). CLMET3.1 is a principled collection of public domain 
- texts drawn from various online archiving projects. """
-
-import os
-import xml.etree.ElementTree as ET
-import datasets
-from bs4 import BeautifulSoup
-
-
-_CITATION = """@article{de2015corpus,
-  title={Corpus of Late Modern English texts (version 3.1)},
-  author={De Smet, Hendrik and Flach, Susanne and Tyrkk{\"o}, Jukka and Diller, Hans-J{\"u}rgen},
-  year={2015}
-}
-"""
-
-_DESCRIPTION = """The Corpus of Late Modern English Texts, version 3.1 (CLMET3.1) has been created by Hendrik De Smet, 
-Susanne Flach, Hans-Jürgen Diller and Jukka Tyrkkö, as an offshoot of a bigger project developing a database of text 
-descriptors (Diller, De Smet & Tyrkkö 2011). CLMET3.1 is a principled collection of public domain texts drawn from 
-various online archiving projects. This dataset can be used for part-of-speech tagging, NER and text classification
-"""
-
-_HOMEPAGE = "http://fedora.clarin-d.uni-saarland.de/clmet/clmet.html"
-
-_LICENSE = "Creative Commons Attribution Non Commercial Share Alike 4.0 International"
-
-_DATASETNAME = "clmet"
-
-_URLS = {
-    _DATASETNAME: "http://fedora.clarin-d.uni-saarland.de/clmet/clmet3_1.zip",
-}
-
-_POS_LIST = [
-    "CC",
-    "CD",
-    "DT",
-    "EX",
-    "FW",
-    "IN",
-    "JJ",
-    "JJR",
-    "JJS",
-    "MD",
-    "NN",
-    "NNS",
-    "NP",
-    "NPS",
-    "PDT",
-    "POS",
-    "PP",
-    "PP$",
-    "RB",
-    "RBR",
-    "RBS",
-    "RP",
-    "SENT",
-    "SYM",
-    "TO",
-    "UH",
-    "VB",
-    "VBD",
-    "VBG",
-    "VBN",
-    "VBZ",
-    "VBP",
-    "WDT",
-    "WP",
-    "WP$",
-    "WRB",
-    "XX0",
-    "CURR",
-    "PUN",
-    "LQUO",
-    "RQUO",
-    "BRL",
-    "BRR",
-    "LS",
-]
-_POS_LOOKUP = {tag: idx for idx, tag in enumerate(_POS_LIST)}
-_CLASS_LIST = [
-    "ADJ",
-    "ADV",
-    "ART",
-    "CONJ",
-    "INTJ",
-    "PREP",
-    "PRON",
-    "PUNC",
-    "SUBST",
-    "SYM",
-    "UNC",
-    "VERB",
-    "QUOT"
-]
-_CLASS_LOOKUP = {tag: idx for idx, tag in enumerate(_CLASS_LIST)}
-logger = datasets.utils.logging.get_logger(__name__)
-
-
-class CLMET_3_1(datasets.GeneratorBasedBuilder):
-    """"""
-
-    VERSION = datasets.Version("3.1.0")
-
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="plain",
-            version=VERSION,
-            description="This format contains text as single string and the classifications",
-        ),
-        datasets.BuilderConfig(
-            name="class",
-            version=VERSION,
-            description="This format contains the text as a list of tokens, annotated according to the simplified Oxford wordclass tags",
-        ),
-        datasets.BuilderConfig(
-            name="pos",
-            version=VERSION,
-            description="This format contains the text as a list of tokens, annotated according to the Penn Treebank POS tags",
-        ),
-    ]
-
-    DEFAULT_CONFIG_NAME = "plain"
-
-    def _info(self):
-        if self.config.name == "plain":
-            features = datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "genre": datasets.Value("string"),
-                    "subgenre": datasets.Value("string"),
-                    "year": datasets.Value("string"),
-                    "quarter_cent": datasets.Value("string"),
-                    "decade": datasets.Value("string"),
-                    "title": datasets.Value("string"),
-                    "author": datasets.Value("string"),
-                    "notes": datasets.Value("string"),
-                    "comments": datasets.Value("string"),
-                    "period": datasets.Value("string"),
-                    "id": datasets.Value("string"),
-                }
-            )
-        elif self.config.name == "class":
-            logger.warn(f"CLASS tags are as follows: {_CLASS_LIST}")
-            features = datasets.Features(
-                {
-                    "text": datasets.Sequence(datasets.Value("string")),
-                    "pos_tags": datasets.Sequence(datasets.Value("int32")),
-                    "genre": datasets.Value("string"),
-                    "subgenre": datasets.Value("string"),
-                    "year": datasets.Value("string"),
-                    "quarter_cent": datasets.Value("string"),
-                    "decade": datasets.Value("string"),
-                    "title": datasets.Value("string"),
-                    "author": datasets.Value("string"),
-                    "notes": datasets.Value("string"),
-                    "comments": datasets.Value("string"),
-                    "period": datasets.Value("string"),
-                    "id": datasets.Value("string"),
-                }
-            )
-        elif self.config.name == "pos":
-            logger.warn(f"POS tags are as follows: {_POS_LIST}")
-            features = datasets.Features(
-                {
-                    "text": datasets.Sequence(datasets.Value("string")),
-                    "pos_tags": datasets.Sequence(datasets.Value("int32")),
-                    "genre": datasets.Value("string"),
-                    "subgenre": datasets.Value("string"),
-                    "year": datasets.Value("string"),
-                    "quarter_cent": datasets.Value("string"),
-                    "decade": datasets.Value("string"),
-                    "title": datasets.Value("string"),
-                    "author": datasets.Value("string"),
-                    "notes": datasets.Value("string"),
-                    "comments": datasets.Value("string"),
-                    "period": datasets.Value("string"),
-                    "id": 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)
-        data_dir = os.path.join(data_dir, "clmet", "corpus", "txt")
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
-                gen_kwargs={
-                    "data_dir": data_dir,
-                    "split": "train",
-                },
-            ),
-        ]
-
-    def parse_pos_text(self, content_parts, pos_type):
-        tokens = []
-        pos_tags = []
-        unknown_tag = False
-        malformed_token = False
-        for content_part in content_parts:
-            text = content_part.text.strip()
-            for text_part in text.split():
-                try:
-                    token, pos_tag = text_part.split("_")
-                    pos_tag = pos_tag.replace("\n", "").strip().upper()
-                    if pos_type == "pos":
-                        pos_tag_idx = _POS_LOOKUP.get(pos_tag,-1)
-                    else:
-                        pos_tag_idx = _CLASS_LOOKUP.get(pos_tag,-1)
-                    if pos_tag_idx==-1:
-                        unknown_tag = True
-                    tokens.append(token)
-                    pos_tags.append(pos_tag_idx)
-                except Exception as e:
-                    malformed_token = True
-        return tokens, pos_tags, unknown_tag, malformed_token
-
-    def parse_file(self, file, pos_type):
-        with open(file, "r", encoding="utf-8") as fp:
-            soup = BeautifulSoup(fp, features="html.parser")
-            id = soup.id.text
-            period = soup.period.text
-            quarter_cent = soup.quartcent.text
-            decade = soup.decade.text
-            year = soup.year.text
-            genre = soup.genre.text
-            subgenre = soup.subgenre.text
-            title = soup.title.text
-            notes = soup.notes.text
-            comments = soup.comments.text
-            author = soup.author.text
-            data_point = {
-                "id": id,
-                "period": period,
-                "genre": genre,
-                "subgenre": subgenre,
-                "decade": decade,
-                "quarter_cent": quarter_cent,
-                "title": title,
-                "notes": notes if notes else "",
-                "comments": comments if comments else "",
-                "author": author,
-                "year": year,
-            }
-            content_parts = soup.find("text").find_all("p")
-
-            if pos_type in ["pos", "class"]:
-                content = self.parse_pos_text(content_parts, pos_type)
-                if content[2]:
-                    logger.warn(f'Unknown tag in sample {id}')
-                if content[3]:
-                    logger.warn(f'Malformed token in sample {id}')
-                data_point["text"] = content[0]
-                data_point["pos_tags"] = content[1]
-            else:
-                content = []
-                for content_part in content_parts:
-                    content.append(content_part.text)
-                content = " ".join(content)
-                data_point["text"] = content
-            return (id, data_point)
-
-    def _generate_examples(self, data_dir, split):
-        final_data_dir = os.path.join(data_dir, self.config.name)
-        for file in os.listdir(final_data_dir):
-            id, data = self.parse_file(
-                os.path.join(final_data_dir, file), self.config.name
-            )
-            yield id, data

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