draft loading script

README.md

@@ -1,3 +1,112 @@
 ---
 license: cc-by-4.0
+dataset_info:
+  features:
+  - name: tokens
+    sequence: string
+  - name: NE-MAIN
+    sequence:
+      class_label:
+        names:
+          '0': B-Organization
+          '1': B-Organization,B-Place
+          '2': B-Organization,I-Person
+          '3': B-Organization,I-Place
+          '4': B-Person
+          '5': B-Person,B-Place
+          '6': B-Person,I-Place
+          '7': B-Place
+          '8': I-Organization
+          '9': I-Organization,B-Place
+          '10': I-Organization,I-Person
+          '11': I-Organization,I-Person,B-Place
+          '12': I-Organization,I-Person,I-Place
+          '13': I-Organization,I-Place
+          '14': I-Person
+          '15': I-Person,B-Place
+          '16': I-Person,I-Place
+          '17': I-Place
+          '18': O
+  - name: NE-PER-NAME
+    sequence:
+      class_label:
+        names:
+          '0': I-ProperName
+          '1': O
+          '2': B-ProperName
+          '3': ''
+  - name: NE-PER-GENDER
+    sequence:
+      class_label:
+        names:
+          '0': B-Group
+          '1': B-Man
+          '2': B-Man,B-Unspecified
+          '3': B-Man,I-Woman
+          '4': B-Unspecified
+          '5': B-Unspecified,I-Woman
+          '6': B-Woman
+          '7': I-Group
+          '8': I-Man
+          '9': I-Man,I-Unspecified
+          '10': I-Man,I-Woman
+          '11': I-Unspecified
+          '12': I-Unspecified,I-Woman
+          '13': I-Woman
+          '14': NE-PER-GENDER
+          '15': O
+  - name: NE-PER-LEGAL-STATUS
+    sequence:
+      class_label:
+        names:
+          '0': B-Enslaved
+          '1': B-Freed
+          '2': B-Unspecified
+          '3': I-Enslaved
+          '4': I-Freed
+          '5': I-Unspecified
+          '6': NE-PER-LEGAL-STATUS
+          '7': O
+  - name: NE-PER-ROLE
+    sequence:
+      class_label:
+        names:
+          '0': B-Acting_Notary
+          '1': B-Beneficiary
+          '2': B-Notary
+          '3': B-Other
+          '4': B-Testator
+          '5': B-Testator_Beneficiary
+          '6': B-Witness
+          '7': I-Acting_Notary
+          '8': I-Beneficiary
+          '9': I-Beneficiary,B-Other
+          '10': I-Beneficiary,I-Other
+          '11': I-Notary
+          '12': I-Other
+          '13': I-Testator
+          '14': I-Testator_Beneficiary
+          '15': I-Witness
+          '16': NE-PER-ROLE
+          '17': O
+  - name: NE-ORG-BENEFICIARY
+    sequence:
+      class_label:
+        names:
+          '0': B-No
+          '1': B-Yes
+          '2': I-No
+          '3': I-Yes
+          '4': NE-ORG-BENEFICIARY
+          '5': O
+  - name: MISC
+    dtype: string
+  - name: document_id
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 31436367
+    num_examples: 2199
+  download_size: 12669993
+  dataset_size: 31436367
 ---

unsilence_voc.py

@@ -0,0 +1,232 @@
+# coding=utf-8
+# Copyright 2022 HuggingFace Datasets Authors.
+#
+# 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.
+
+# Lint as: python3
+"""UnSilenceVOC dataset"""
+
+
+import datasets
+import re
+from datasets import ClassLabel, Sequence, Value
+
+
+_CITATION = """\
+TODO
+"""
+
+_DESCRIPTION = """\
+TODO
+"""
+
+NE_MAIN_LABELS = [
+    "B-Organization",
+    "B-Organization,B-Place",
+    "B-Organization,I-Person",
+    "B-Organization,I-Place",
+    "B-Person",
+    "B-Person,B-Place",
+    "B-Person,I-Place",
+    "B-Place",
+    "I-Organization",
+    "I-Organization,B-Place",
+    "I-Organization,I-Person",
+    "I-Organization,I-Person,B-Place",
+    "I-Organization,I-Person,I-Place",
+    "I-Organization,I-Place",
+    "I-Person",
+    "I-Person,B-Place",
+    "I-Person,I-Place",
+    "I-Place",
+    "O",
+]
+
+NE_PER_NAME = ["I-ProperName", "O", "B-ProperName", ""]
+NE_PER_GENDER = [
+    "B-Group",
+    "B-Man",
+    "B-Man,B-Unspecified",
+    "B-Man,I-Woman",
+    "B-Unspecified",
+    "B-Unspecified,I-Woman",
+    "B-Woman",
+    "I-Group",
+    "I-Man",
+    "I-Man,I-Unspecified",
+    "I-Man,I-Woman",
+    "I-Unspecified",
+    "I-Unspecified,I-Woman",
+    "I-Woman",
+    "NE-PER-GENDER",
+    "O",
+]
+
+NE_PER_LEGAL_STATUS = [
+    "B-Enslaved",
+    "B-Freed",
+    "B-Unspecified",
+    "I-Enslaved",
+    "I-Freed",
+    "I-Unspecified",
+    "NE-PER-LEGAL-STATUS",
+    "O",
+]
+
+NE_PER_ROLE = [
+    "B-Acting_Notary",
+    "B-Beneficiary",
+    "B-Notary",
+    "B-Other",
+    "B-Testator",
+    "B-Testator_Beneficiary",
+    "B-Witness",
+    "I-Acting_Notary",
+    "I-Beneficiary",
+    "I-Beneficiary,B-Other",
+    "I-Beneficiary,I-Other",
+    "I-Notary",
+    "I-Other",
+    "I-Testator",
+    "I-Testator_Beneficiary",
+    "I-Witness",
+    "NE-PER-ROLE",
+    "O",
+]
+
+NE_ORG_BENEFICIARY = [
+    "B-No",
+    "B-Yes",
+    "I-No",
+    "I-Yes",
+    "NE-ORG-BENEFICIARY",
+    "O",
+]
+
+_BASE_URL = (
+    "https://raw.githubusercontent.com/budh333/UnSilence_VOC/main/processed_data"
+)
+
+_URLS = {
+    "train": f"{_BASE_URL}/train-nl.tsv",
+    "test": f"{_BASE_URL}/test-nl.tsv",
+    "dev": f"{_BASE_URL}/dev-nl.tsv",
+}
+
+
+class UnSilenceVOC(datasets.GeneratorBasedBuilder):
+    """UnSilence VOC dataset."""
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "tokens": Sequence(datasets.Value("string")),
+                    "NE-MAIN": Sequence(
+                        ClassLabel(names=NE_MAIN_LABELS),
+                    ),
+                    "NE-PER-NAME": Sequence(ClassLabel(names=NE_PER_NAME)),
+                    "NE-PER-GENDER": Sequence(ClassLabel(names=NE_PER_GENDER)),
+                    "NE-PER-LEGAL-STATUS": Sequence(
+                        ClassLabel(names=NE_PER_LEGAL_STATUS)
+                    ),
+                    "NE-PER-ROLE": Sequence(ClassLabel(names=NE_PER_ROLE)),
+                    "NE-ORG-BENEFICIARY": Sequence(
+                        ClassLabel(names=NE_ORG_BENEFICIARY)
+                    ),
+                    "MISC": Value("string"),
+                    "document_id": datasets.Value("string"),
+                }
+            ),
+            homepage="TODO",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        downloaded_files = dl_manager.download_and_extract(_URLS)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": downloaded_files["train"]},
+            )
+        ]
+
+    def _generate_examples(self, filepath):
+        document_id_re = re.compile(r"# document_path = ..(\/.*.txt)")
+        with open(filepath, encoding="utf-8") as f:
+            guid = 0
+            tokens = []
+            NE_MAIN_LABELS = []
+            NE_PER_NAME = []
+            NE_PER_GENDER = []
+            NE_PER_LEGAL_STATUS = []
+            NE_PER_ROLE = []
+            NE_ORG_BENEFICIARY = []
+            MISC = []
+
+            for line in f:
+                if line.startswith("TOKEN"):
+                    continue
+                if line.startswith("#") or line.startswith("\t"):
+                    document_id_match = re.search(document_id_re, line)
+                    if document_id_match:
+                        document_id = document_id_match.groups(0)[0]
+
+                    if not tokens:
+                        continue
+                    yield guid, {
+                        "tokens": tokens,
+                        "NE-MAIN": NE_MAIN_LABELS,
+                        "NE-PER-NAME": NE_PER_NAME,
+                        "NE-PER-GENDER": NE_PER_GENDER,
+                        "NE-PER-LEGAL-STATUS": NE_PER_LEGAL_STATUS,
+                        "NE-PER-ROLE": NE_PER_ROLE,
+                        "NE-ORG-BENEFICIARY": NE_ORG_BENEFICIARY,
+                        "MISC": MISC,
+                        "document_id": document_id,
+                    }
+                    guid += 1
+                    tokens = []
+                    NE_MAIN_LABELS = []
+                    NE_PER_NAME = []
+                    NE_PER_GENDER = []
+                    NE_PER_LEGAL_STATUS = []
+                    NE_PER_ROLE = []
+                    NE_ORG_BENEFICIARY = []
+                    MISC = []
+                else:
+                    # tokens are tab separated
+                    splits = line.split("\t")
+                    tokens.append(splits[0])
+                    NE_MAIN_LABELS.append(splits[1])
+                    NE_PER_NAME.append(splits[2])
+                    NE_PER_GENDER.append(splits[3])
+                    NE_PER_LEGAL_STATUS.append(splits[4])
+                    NE_PER_ROLE.append(splits[5])
+                    NE_ORG_BENEFICIARY.append(splits[6])
+                    MISC.append(splits[-1].replace("\n", ""))
+
+            # last example
+            yield guid, {
+                "tokens": tokens,
+                "NE-MAIN": NE_MAIN_LABELS,
+                "NE-PER-NAME": NE_PER_NAME,
+                "NE-PER-GENDER": NE_PER_GENDER,
+                "NE-PER-LEGAL-STATUS": NE_PER_LEGAL_STATUS,
+                "NE-PER-ROLE": NE_PER_ROLE,
+                "NE-ORG-BENEFICIARY": NE_ORG_BENEFICIARY,
+                "MISC": MISC,
+                "document_id": "document_id",
+            }