Datasets:
conllpp

Task Categories: token-classification
Languages: English
Multilinguality: monolingual
Size Categories: 10K<n<100K
Language Creators: found
Annotations Creators: expert-generated
Source Datasets: extended|conll2003
Licenses: unknown
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Update files from the datasets library (from 1.5.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.5.0

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README.md ADDED
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1
+ ---
2
+ annotations_creators:
3
+ - expert-generated
4
+ language_creators:
5
+ - found
6
+ languages:
7
+ - en
8
+ licenses:
9
+ - unknown
10
+ multilinguality:
11
+ - monolingual
12
+ size_categories:
13
+ - 10K<n<100K
14
+ source_datasets:
15
+ - extended|conll2003
16
+ task_categories:
17
+ - structure-prediction
18
+ task_ids:
19
+ - named-entity-recognition
20
+ ---
21
+
22
+ # Dataset Card for "conllpp"
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+
24
+ ## Table of Contents
25
+ - [Dataset Card for conllpp](#dataset-card-for-dataset-name)
26
+ - [Table of Contents](#table-of-contents)
27
+ - [Dataset Description](#dataset-description)
28
+ - [Dataset Summary](#dataset-summary)
29
+ - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
30
+ - [Languages](#languages)
31
+ - [Dataset Structure](#dataset-structure)
32
+ - [Data Instances](#data-instances)
33
+ - [Data Fields](#data-fields)
34
+ - [Data Splits](#data-splits)
35
+ - [Dataset Creation](#dataset-creation)
36
+ - [Curation Rationale](#curation-rationale)
37
+ - [Source Data](#source-data)
38
+ - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
39
+ - [Who are the source language producers?](#who-are-the-source-language-producers)
40
+ - [Annotations](#annotations)
41
+ - [Annotation process](#annotation-process)
42
+ - [Who are the annotators?](#who-are-the-annotators)
43
+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
44
+ - [Considerations for Using the Data](#considerations-for-using-the-data)
45
+ - [Social Impact of Dataset](#social-impact-of-dataset)
46
+ - [Discussion of Biases](#discussion-of-biases)
47
+ - [Other Known Limitations](#other-known-limitations)
48
+ - [Additional Information](#additional-information)
49
+ - [Dataset Curators](#dataset-curators)
50
+ - [Licensing Information](#licensing-information)
51
+ - [Citation Information](#citation-information)
52
+ - [Contributions](#contributions)
53
+
54
+ ## Dataset Description
55
+
56
+ - **Homepage:** [Github](https://github.com/ZihanWangKi/CrossWeigh)
57
+ - **Repository:** [Github](https://github.com/ZihanWangKi/CrossWeigh)
58
+ - **Paper:** [Aclweb](https://www.aclweb.org/anthology/D19-1519)
59
+ - **Leaderboard:**
60
+ - **Point of Contact:**
61
+
62
+ ### Dataset Summary
63
+
64
+ CoNLLpp is a corrected version of the CoNLL2003 NER dataset where labels of 5.38% of the sentences in the test set
65
+ have been manually corrected. The training set and development set from CoNLL2003 is included for completeness. One
66
+ correction on the test set for example, is:
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+
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+ ```
69
+ {
70
+ "tokens": ["SOCCER", "-", "JAPAN", "GET", "LUCKY", "WIN", ",", "CHINA", "IN", "SURPRISE", "DEFEAT", "."],
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+ "original_ner_tags_in_conll2003": ["O", "O", "B-LOC", "O", "O", "O", "O", "B-PER", "O", "O", "O", "O"],
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+ "corrected_ner_tags_in_conllpp": ["O", "O", "B-LOC", "O", "O", "O", "O", "B-LOC", "O", "O", "O", "O"],
73
+ }
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+ ```
75
+
76
+ ### Supported Tasks and Leaderboards
77
+
78
+ [More Information Needed]
79
+
80
+ ### Languages
81
+
82
+ [More Information Needed]
83
+
84
+ ## Dataset Structure
85
+
86
+ We show detailed information for up to 5 configurations of the dataset.
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+
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+ ### Data Instances
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+
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+ #### conllpp
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+
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+ - **Size of downloaded dataset files:** 4.63 MB
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+ - **Size of the generated dataset:** 9.78 MB
94
+ - **Total amount of disk used:** 14.41 MB
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+
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+ An example of 'train' looks as follows.
97
+ ```
98
+ This example was too long and was cropped:
99
+
100
+ {
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+ "chunk_tags": [11, 12, 12, 21, 13, 11, 11, 21, 13, 11, 12, 13, 11, 21, 22, 11, 12, 17, 11, 21, 17, 11, 12, 12, 21, 22, 22, 13, 11, 0],
102
+ "id": "0",
103
+ "ner_tags": [0, 3, 4, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
104
+ "pos_tags": [12, 22, 22, 38, 15, 22, 28, 38, 15, 16, 21, 35, 24, 35, 37, 16, 21, 15, 24, 41, 15, 16, 21, 21, 20, 37, 40, 35, 21, 7],
105
+ "tokens": ["The", "European", "Commission", "said", "on", "Thursday", "it", "disagreed", "with", "German", "advice", "to", "consumers", "to", "shun", "British", "lamb", "until", "scientists", "determine", "whether", "mad", "cow", "disease", "can", "be", "transmitted", "to", "sheep", "."]
106
+ }
107
+ ```
108
+
109
+ ### Data Fields
110
+
111
+ The data fields are the same among all splits.
112
+
113
+ #### conllpp
114
+ - `id`: a `string` feature.
115
+ - `tokens`: a `list` of `string` features.
116
+ - `pos_tags`: a `list` of classification labels, with possible values including `"` (0), `''` (1), `#` (2), `$` (3), `(` (4).
117
+ - `chunk_tags`: a `list` of classification labels, with possible values including `O` (0), `B-ADJP` (1), `I-ADJP` (2), `B-ADVP` (3), `I-ADVP` (4).
118
+ - `ner_tags`: a `list` of classification labels, with possible values including `O` (0), `B-PER` (1), `I-PER` (2), `B-ORG` (3), `I-ORG` (4).
119
+
120
+ ### Data Splits Sample Size
121
+
122
+ | name |train|validation|test|
123
+ |---------|----:|---------:|---:|
124
+ |conll2003|14041| 3250|3453|
125
+
126
+ ## Dataset Creation
127
+
128
+ ### Curation Rationale
129
+
130
+ [More Information Needed]
131
+
132
+ ### Source Data
133
+
134
+ #### Initial Data Collection and Normalization
135
+
136
+ [More Information Needed]
137
+
138
+ #### Who are the source language producers?
139
+
140
+ [More Information Needed]
141
+
142
+ ### Annotations
143
+
144
+ #### Annotation process
145
+
146
+ [More Information Needed]
147
+
148
+ #### Who are the annotators?
149
+
150
+ [More Information Needed]
151
+
152
+ ### Personal and Sensitive Information
153
+
154
+ [More Information Needed]
155
+
156
+ ## Considerations for Using the Data
157
+
158
+ ### Social Impact of Dataset
159
+
160
+ [More Information Needed]
161
+
162
+ ### Discussion of Biases
163
+
164
+ [More Information Needed]
165
+
166
+ ### Other Known Limitations
167
+
168
+ [More Information Needed]
169
+
170
+ ## Additional Information
171
+
172
+ ### Dataset Curators
173
+
174
+ [More Information Needed]
175
+
176
+ ### Licensing Information
177
+
178
+ [More Information Needed]
179
+
180
+ ### Citation Information
181
+
182
+ [More Information Needed]
183
+
184
+ ### Contributions
185
+
186
+ Thanks to [@ZihanWangKi](https://github.com/ZihanWangKi) for adding this dataset.
conllpp.py ADDED
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1
+ # coding=utf-8
2
+ # Copyright 2020 HuggingFace Datasets Authors.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+
16
+ # Lint as: python3
17
+ """CrossWeigh: Training Named Entity Tagger from Imperfect Annotations"""
18
+
19
+ import logging
20
+
21
+ import datasets
22
+
23
+
24
+ _CITATION = """\
25
+ @inproceedings{wang2019crossweigh,
26
+ title={CrossWeigh: Training Named Entity Tagger from Imperfect Annotations},
27
+ author={Wang, Zihan and Shang, Jingbo and Liu, Liyuan and Lu, Lihao and Liu, Jiacheng and Han, Jiawei},
28
+ 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)},
29
+ pages={5157--5166},
30
+ year={2019}
31
+ }
32
+ """
33
+
34
+ _DESCRIPTION = """\
35
+ CoNLLpp is a corrected version of the CoNLL2003 NER dataset where labels of 5.38% of the sentences in the test set
36
+ have been manually corrected. The training set and development set are included for completeness.
37
+ For more details see https://www.aclweb.org/anthology/D19-1519/ and https://github.com/ZihanWangKi/CrossWeigh
38
+ """
39
+
40
+ _URL = "https://github.com/ZihanWangKi/CrossWeigh/raw/master/data/"
41
+ _TRAINING_FILE = "conllpp_train.txt"
42
+ _DEV_FILE = "conllpp_dev.txt"
43
+ _TEST_FILE = "conllpp_test.txt"
44
+
45
+
46
+ class ConllppConfig(datasets.BuilderConfig):
47
+ """BuilderConfig for Conll2003"""
48
+
49
+ def __init__(self, **kwargs):
50
+ """BuilderConfig forConll2003.
51
+ Args:
52
+ **kwargs: keyword arguments forwarded to super.
53
+ """
54
+ super(ConllppConfig, self).__init__(**kwargs)
55
+
56
+
57
+ class Conllpp(datasets.GeneratorBasedBuilder):
58
+ """Conllpp dataset."""
59
+
60
+ BUILDER_CONFIGS = [
61
+ ConllppConfig(name="conllpp", version=datasets.Version("1.0.0"), description="Conllpp dataset"),
62
+ ]
63
+
64
+ def _info(self):
65
+ return datasets.DatasetInfo(
66
+ description=_DESCRIPTION,
67
+ features=datasets.Features(
68
+ {
69
+ "id": datasets.Value("string"),
70
+ "tokens": datasets.Sequence(datasets.Value("string")),
71
+ "pos_tags": datasets.Sequence(
72
+ datasets.features.ClassLabel(
73
+ names=[
74
+ '"',
75
+ "''",
76
+ "#",
77
+ "$",
78
+ "(",
79
+ ")",
80
+ ",",
81
+ ".",
82
+ ":",
83
+ "``",
84
+ "CC",
85
+ "CD",
86
+ "DT",
87
+ "EX",
88
+ "FW",
89
+ "IN",
90
+ "JJ",
91
+ "JJR",
92
+ "JJS",
93
+ "LS",
94
+ "MD",
95
+ "NN",
96
+ "NNP",
97
+ "NNPS",
98
+ "NNS",
99
+ "NN|SYM",
100
+ "PDT",
101
+ "POS",
102
+ "PRP",
103
+ "PRP$",
104
+ "RB",
105
+ "RBR",
106
+ "RBS",
107
+ "RP",
108
+ "SYM",
109
+ "TO",
110
+ "UH",
111
+ "VB",
112
+ "VBD",
113
+ "VBG",
114
+ "VBN",
115
+ "VBP",
116
+ "VBZ",
117
+ "WDT",
118
+ "WP",
119
+ "WP$",
120
+ "WRB",
121
+ ]
122
+ )
123
+ ),
124
+ "chunk_tags": datasets.Sequence(
125
+ datasets.features.ClassLabel(
126
+ names=[
127
+ "O",
128
+ "B-ADJP",
129
+ "I-ADJP",
130
+ "B-ADVP",
131
+ "I-ADVP",
132
+ "B-CONJP",
133
+ "I-CONJP",
134
+ "B-INTJ",
135
+ "I-INTJ",
136
+ "B-LST",
137
+ "I-LST",
138
+ "B-NP",
139
+ "I-NP",
140
+ "B-PP",
141
+ "I-PP",
142
+ "B-PRT",
143
+ "I-PRT",
144
+ "B-SBAR",
145
+ "I-SBAR",
146
+ "B-UCP",
147
+ "I-UCP",
148
+ "B-VP",
149
+ "I-VP",
150
+ ]
151
+ )
152
+ ),
153
+ "ner_tags": datasets.Sequence(
154
+ datasets.features.ClassLabel(
155
+ names=[
156
+ "O",
157
+ "B-PER",
158
+ "I-PER",
159
+ "B-ORG",
160
+ "I-ORG",
161
+ "B-LOC",
162
+ "I-LOC",
163
+ "B-MISC",
164
+ "I-MISC",
165
+ ]
166
+ )
167
+ ),
168
+ }
169
+ ),
170
+ supervised_keys=None,
171
+ homepage="https://github.com/ZihanWangKi/CrossWeigh",
172
+ citation=_CITATION,
173
+ )
174
+
175
+ def _split_generators(self, dl_manager):
176
+ """Returns SplitGenerators."""
177
+ urls_to_download = {
178
+ "train": f"{_URL}{_TRAINING_FILE}",
179
+ "dev": f"{_URL}{_DEV_FILE}",
180
+ "test": f"{_URL}{_TEST_FILE}",
181
+ }
182
+ downloaded_files = dl_manager.download_and_extract(urls_to_download)
183
+
184
+ return [
185
+ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
186
+ datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
187
+ datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
188
+ ]
189
+
190
+ def _generate_examples(self, filepath):
191
+ logging.info("⏳ Generating examples from = %s", filepath)
192
+ with open(filepath, encoding="utf-8") as f:
193
+ guid = 0
194
+ tokens = []
195
+ pos_tags = []
196
+ chunk_tags = []
197
+ ner_tags = []
198
+ for line in f:
199
+ if line.startswith("-DOCSTART-") or line == "" or line == "\n":
200
+ if tokens:
201
+ yield guid, {
202
+ "id": str(guid),
203
+ "tokens": tokens,
204
+ "pos_tags": pos_tags,
205
+ "chunk_tags": chunk_tags,
206
+ "ner_tags": ner_tags,
207
+ }
208
+ guid += 1
209
+ tokens = []
210
+ pos_tags = []
211
+ chunk_tags = []
212
+ ner_tags = []
213
+ else:
214
+ # conll2003 tokens are space separated
215
+ splits = line.split(" ")
216
+ tokens.append(splits[0])
217
+ pos_tags.append(splits[1])
218
+ chunk_tags.append(splits[2])
219
+ ner_tags.append(splits[3].rstrip())
220
+ # last example
221
+ if tokens:
222
+ yield guid, {
223
+ "id": str(guid),
224
+ "tokens": tokens,
225
+ "pos_tags": pos_tags,
226
+ "chunk_tags": chunk_tags,
227
+ "ner_tags": ner_tags,
228
+ }
dataset_infos.json ADDED
@@ -0,0 +1 @@
 
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