Convert dataset to Parquet

README.md

@@ -19,20 +19,8 @@ task_ids:
 - named-entity-recognition
 paperswithcode_id: conll
 pretty_name: CoNLL++
-train-eval-index:
-- config: conllpp
-  task: token-classification
-  task_id: entity_extraction
-  splits:
-    train_split: train
-    eval_split: test
-  col_mapping:
-    tokens: tokens
-    ner_tags: tags
-  metrics:
-  - type: seqeval
-    name: seqeval
 dataset_info:
+  config_name: conllpp
   features:
   - name: id
     dtype: string
@@ -42,106 +30,128 @@ dataset_info:
     sequence:
       class_label:
         names:
-          0: '"'
-          1: ''''''
-          2: '#'
-          3: $
-          4: (
-          5: )
-          6: ','
-          7: .
-          8: ':'
-          9: '``'
-          10: CC
-          11: CD
-          12: DT
-          13: EX
-          14: FW
-          15: IN
-          16: JJ
-          17: JJR
-          18: JJS
-          19: LS
-          20: MD
-          21: NN
-          22: NNP
-          23: NNPS
-          24: NNS
-          25: NN|SYM
-          26: PDT
-          27: POS
-          28: PRP
-          29: PRP$
-          30: RB
-          31: RBR
-          32: RBS
-          33: RP
-          34: SYM
-          35: TO
-          36: UH
-          37: VB
-          38: VBD
-          39: VBG
-          40: VBN
-          41: VBP
-          42: VBZ
-          43: WDT
-          44: WP
-          45: WP$
-          46: WRB
+          '0': '"'
+          '1': ''''''
+          '2': '#'
+          '3': $
+          '4': (
+          '5': )
+          '6': ','
+          '7': .
+          '8': ':'
+          '9': '``'
+          '10': CC
+          '11': CD
+          '12': DT
+          '13': EX
+          '14': FW
+          '15': IN
+          '16': JJ
+          '17': JJR
+          '18': JJS
+          '19': LS
+          '20': MD
+          '21': NN
+          '22': NNP
+          '23': NNPS
+          '24': NNS
+          '25': NN|SYM
+          '26': PDT
+          '27': POS
+          '28': PRP
+          '29': PRP$
+          '30': RB
+          '31': RBR
+          '32': RBS
+          '33': RP
+          '34': SYM
+          '35': TO
+          '36': UH
+          '37': VB
+          '38': VBD
+          '39': VBG
+          '40': VBN
+          '41': VBP
+          '42': VBZ
+          '43': WDT
+          '44': WP
+          '45': WP$
+          '46': WRB
   - name: chunk_tags
     sequence:
       class_label:
         names:
-          0: O
-          1: B-ADJP
-          2: I-ADJP
-          3: B-ADVP
-          4: I-ADVP
-          5: B-CONJP
-          6: I-CONJP
-          7: B-INTJ
-          8: I-INTJ
-          9: B-LST
-          10: I-LST
-          11: B-NP
-          12: I-NP
-          13: B-PP
-          14: I-PP
-          15: B-PRT
-          16: I-PRT
-          17: B-SBAR
-          18: I-SBAR
-          19: B-UCP
-          20: I-UCP
-          21: B-VP
-          22: I-VP
+          '0': O
+          '1': B-ADJP
+          '2': I-ADJP
+          '3': B-ADVP
+          '4': I-ADVP
+          '5': B-CONJP
+          '6': I-CONJP
+          '7': B-INTJ
+          '8': I-INTJ
+          '9': B-LST
+          '10': I-LST
+          '11': B-NP
+          '12': I-NP
+          '13': B-PP
+          '14': I-PP
+          '15': B-PRT
+          '16': I-PRT
+          '17': B-SBAR
+          '18': I-SBAR
+          '19': B-UCP
+          '20': I-UCP
+          '21': B-VP
+          '22': I-VP
   - name: ner_tags
     sequence:
       class_label:
         names:
-          0: O
-          1: B-PER
-          2: I-PER
-          3: B-ORG
-          4: I-ORG
-          5: B-LOC
-          6: I-LOC
-          7: B-MISC
-          8: I-MISC
-  config_name: conllpp
+          '0': O
+          '1': B-PER
+          '2': I-PER
+          '3': B-ORG
+          '4': I-ORG
+          '5': B-LOC
+          '6': I-LOC
+          '7': B-MISC
+          '8': I-MISC
   splits:
   - name: train
-    num_bytes: 6931393
+    num_bytes: 6931345
     num_examples: 14041
   - name: validation
-    num_bytes: 1739247
+    num_bytes: 1739223
     num_examples: 3250
   - name: test
-    num_bytes: 1582078
+    num_bytes: 1582054
     num_examples: 3453
-  download_size: 4859600
-  dataset_size: 10252718
+  download_size: 1807915
+  dataset_size: 10252622
+configs:
+- config_name: conllpp
+  data_files:
+  - split: train
+    path: conllpp/train-*
+  - split: validation
+    path: conllpp/validation-*
+  - split: test
+    path: conllpp/test-*
+  default: true
+train-eval-index:
+- config: conllpp
+  task: token-classification
+  task_id: entity_extraction
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    tokens: tokens
+    ner_tags: tags
+  metrics:
+  - type: seqeval
+    name: seqeval
 ---
 
 # Dataset Card for "conllpp"

conllpp.py

@@ -1,228 +0,0 @@
-# coding=utf-8
-# Copyright 2020 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
-"""CrossWeigh: Training Named Entity Tagger from Imperfect Annotations"""
-
-import logging
-
-import datasets
-
-
-_CITATION = """\
-@inproceedings{wang2019crossweigh,
-  title={CrossWeigh: Training Named Entity Tagger from Imperfect Annotations},
-  author={Wang, Zihan and Shang, Jingbo and Liu, Liyuan and Lu, Lihao and Liu, Jiacheng and Han, Jiawei},
-  booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
-  pages={5157--5166},
-  year={2019}
-}
-"""
-
-_DESCRIPTION = """\
-CoNLLpp is a corrected version of the CoNLL2003 NER dataset where labels of 5.38% of the sentences in the test set
-have been manually corrected. The training set and development set are included for completeness.
-For more details see https://www.aclweb.org/anthology/D19-1519/ and https://github.com/ZihanWangKi/CrossWeigh
-"""
-
-_URL = "https://github.com/ZihanWangKi/CrossWeigh/raw/master/data/"
-_TRAINING_FILE = "conllpp_train.txt"
-_DEV_FILE = "conllpp_dev.txt"
-_TEST_FILE = "conllpp_test.txt"
-
-
-class ConllppConfig(datasets.BuilderConfig):
-    """BuilderConfig for Conll2003"""
-
-    def __init__(self, **kwargs):
-        """BuilderConfig forConll2003.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(ConllppConfig, self).__init__(**kwargs)
-
-
-class Conllpp(datasets.GeneratorBasedBuilder):
-    """Conllpp dataset."""
-
-    BUILDER_CONFIGS = [
-        ConllppConfig(name="conllpp", version=datasets.Version("1.0.0"), description="Conllpp dataset"),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "id": datasets.Value("string"),
-                    "tokens": datasets.Sequence(datasets.Value("string")),
-                    "pos_tags": datasets.Sequence(
-                        datasets.features.ClassLabel(
-                            names=[
-                                '"',
-                                "''",
-                                "#",
-                                "$",
-                                "(",
-                                ")",
-                                ",",
-                                ".",
-                                ":",
-                                "``",
-                                "CC",
-                                "CD",
-                                "DT",
-                                "EX",
-                                "FW",
-                                "IN",
-                                "JJ",
-                                "JJR",
-                                "JJS",
-                                "LS",
-                                "MD",
-                                "NN",
-                                "NNP",
-                                "NNPS",
-                                "NNS",
-                                "NN|SYM",
-                                "PDT",
-                                "POS",
-                                "PRP",
-                                "PRP$",
-                                "RB",
-                                "RBR",
-                                "RBS",
-                                "RP",
-                                "SYM",
-                                "TO",
-                                "UH",
-                                "VB",
-                                "VBD",
-                                "VBG",
-                                "VBN",
-                                "VBP",
-                                "VBZ",
-                                "WDT",
-                                "WP",
-                                "WP$",
-                                "WRB",
-                            ]
-                        )
-                    ),
-                    "chunk_tags": datasets.Sequence(
-                        datasets.features.ClassLabel(
-                            names=[
-                                "O",
-                                "B-ADJP",
-                                "I-ADJP",
-                                "B-ADVP",
-                                "I-ADVP",
-                                "B-CONJP",
-                                "I-CONJP",
-                                "B-INTJ",
-                                "I-INTJ",
-                                "B-LST",
-                                "I-LST",
-                                "B-NP",
-                                "I-NP",
-                                "B-PP",
-                                "I-PP",
-                                "B-PRT",
-                                "I-PRT",
-                                "B-SBAR",
-                                "I-SBAR",
-                                "B-UCP",
-                                "I-UCP",
-                                "B-VP",
-                                "I-VP",
-                            ]
-                        )
-                    ),
-                    "ner_tags": datasets.Sequence(
-                        datasets.features.ClassLabel(
-                            names=[
-                                "O",
-                                "B-PER",
-                                "I-PER",
-                                "B-ORG",
-                                "I-ORG",
-                                "B-LOC",
-                                "I-LOC",
-                                "B-MISC",
-                                "I-MISC",
-                            ]
-                        )
-                    ),
-                }
-            ),
-            supervised_keys=None,
-            homepage="https://github.com/ZihanWangKi/CrossWeigh",
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        urls_to_download = {
-            "train": f"{_URL}{_TRAINING_FILE}",
-            "dev": f"{_URL}{_DEV_FILE}",
-            "test": f"{_URL}{_TEST_FILE}",
-        }
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        logging.info("⏳ Generating examples from = %s", filepath)
-        with open(filepath, encoding="utf-8") as f:
-            guid = 0
-            tokens = []
-            pos_tags = []
-            chunk_tags = []
-            ner_tags = []
-            for line in f:
-                if line.startswith("-DOCSTART-") or line == "" or line == "\n":
-                    if tokens:
-                        yield guid, {
-                            "id": str(guid),
-                            "tokens": tokens,
-                            "pos_tags": pos_tags,
-                            "chunk_tags": chunk_tags,
-                            "ner_tags": ner_tags,
-                        }
-                        guid += 1
-                        tokens = []
-                        pos_tags = []
-                        chunk_tags = []
-                        ner_tags = []
-                else:
-                    # conll2003 tokens are space separated
-                    splits = line.split(" ")
-                    tokens.append(splits[0])
-                    pos_tags.append(splits[1])
-                    chunk_tags.append(splits[2])
-                    ner_tags.append(splits[3].rstrip())
-            # last example
-            if tokens:
-                yield guid, {
-                    "id": str(guid),
-                    "tokens": tokens,
-                    "pos_tags": pos_tags,
-                    "chunk_tags": chunk_tags,
-                    "ner_tags": ner_tags,
-                }

conllpp/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
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+size 276767

conllpp/train-00000-of-00001.parquet

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+oid sha256:d4264892ad73c70e95f85b55754158a4b4269fed152121a31447a973597ceb19
+size 1221036

conllpp/validation-00000-of-00001.parquet

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+oid sha256:656885266739f8ab503bd89da609b53409a00541aa89603c81804762cafa9803
+size 310112