File size: 8,947 Bytes
a4b90e0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8a79cf1
 
 
a4b90e0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fba7825
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a4b90e0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8a79cf1
a4b90e0
 
 
 
fba7825
 
a4b90e0
 
 
 
 
 
 
 
fba7825
 
a4b90e0
 
 
 
 
fba7825
 
 
 
a4b90e0
 
 
 
 
 
fba7825
 
a4b90e0
 
 
 
 
fba7825
 
a4b90e0
 
 
 
 
 
fba7825
 
a4b90e0
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
# 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
"""The GermEval 2014 NER Shared Task dataset."""


import csv

import datasets


logger = datasets.logging.get_logger(__name__)


_CITATION = """\
@inproceedings{benikova-etal-2014-nosta,
    title = {NoSta-D Named Entity Annotation for German: Guidelines and Dataset},
    author = {Benikova, Darina  and
      Biemann, Chris  and
      Reznicek, Marc},
    booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)},
    month = {may},
    year = {2014},
    address = {Reykjavik, Iceland},
    publisher = {European Language Resources Association (ELRA)},
    url = {http://www.lrec-conf.org/proceedings/lrec2014/pdf/276_Paper.pdf},
    pages = {2524--2531},
}
"""

_DESCRIPTION = """\
The GermEval 2014 NER Shared Task builds on a new dataset with German Named Entity annotation with the following properties:\
    - The data was sampled from German Wikipedia and News Corpora as a collection of citations.\
    - The dataset covers over 31,000 sentences corresponding to over 590,000 tokens.\
    - The NER annotation uses the NoSta-D guidelines, which extend the Tübingen Treebank guidelines,\
      using four main NER categories with sub-structure, and annotating embeddings among NEs\
      such as [ORG FC Kickers [LOC Darmstadt]].
"""

_URLS = {
    "train": "https://drive.google.com/uc?export=download&id=1Jjhbal535VVz2ap4v4r_rN1UEHTdLK5P",
    "dev": "https://drive.google.com/uc?export=download&id=1ZfRcQThdtAR5PPRjIDtrVP7BtXSCUBbm",
    "test": "https://drive.google.com/uc?export=download&id=1u9mb7kNJHWQCWyweMDRMuTFoOHOfeBTH",
}


class GermEval14Config(datasets.BuilderConfig):
    """BuilderConfig for GermEval 2014."""

    def __init__(self, **kwargs):
        """BuilderConfig for GermEval 2014.

        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(GermEval14Config, self).__init__(**kwargs)


class GermEval14(datasets.GeneratorBasedBuilder):
    """GermEval 2014 NER Shared Task dataset."""

    BUILDER_CONFIGS = [
        GermEval14Config(
            name="germeval_14", version=datasets.Version("2.0.0"), description="GermEval 2014 NER Shared Task dataset"
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "id": datasets.Value("string"),
                    "source": datasets.Value("string"),
                    "tokens": datasets.Sequence(datasets.Value("string")),
                    "ner_tags": datasets.Sequence(
                        datasets.features.ClassLabel(
                            names=[
                                "O",
                                "B-LOC",
                                "I-LOC",
                                "B-LOCderiv",
                                "I-LOCderiv",
                                "B-LOCpart",
                                "I-LOCpart",
                                "B-ORG",
                                "I-ORG",
                                "B-ORGderiv",
                                "I-ORGderiv",
                                "B-ORGpart",
                                "I-ORGpart",
                                "B-OTH",
                                "I-OTH",
                                "B-OTHderiv",
                                "I-OTHderiv",
                                "B-OTHpart",
                                "I-OTHpart",
                                "B-PER",
                                "I-PER",
                                "B-PERderiv",
                                "I-PERderiv",
                                "B-PERpart",
                                "I-PERpart",
                            ]
                        )
                    ),
                    "nested_ner_tags": datasets.Sequence(
                        datasets.features.ClassLabel(
                            names=[
                                "O",
                                "B-LOC",
                                "I-LOC",
                                "B-LOCderiv",
                                "I-LOCderiv",
                                "B-LOCpart",
                                "I-LOCpart",
                                "B-ORG",
                                "I-ORG",
                                "B-ORGderiv",
                                "I-ORGderiv",
                                "B-ORGpart",
                                "I-ORGpart",
                                "B-OTH",
                                "I-OTH",
                                "B-OTHderiv",
                                "I-OTHderiv",
                                "B-OTHpart",
                                "I-OTHpart",
                                "B-PER",
                                "I-PER",
                                "B-PERderiv",
                                "I-PERderiv",
                                "B-PERpart",
                                "I-PERpart",
                            ]
                        )
                    ),
                }
            ),
            supervised_keys=None,
            homepage="https://sites.google.com/site/germeval2014ner/",
            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"]}),
            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):
        logger.info("⏳ Generating examples from = %s", filepath)
        with open(filepath, encoding="utf-8") as f:
            data = csv.reader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
            current_source = ""
            current_tokens = []
            current_ner_tags = []
            current_nested_ner_tags = []
            sentence_counter = 0
            for row in data:
                if row:
                    if row[0] == "#":
                        current_source = " ".join(row[1:])
                        continue
                    id_, token, label, nested_label = row[:4]
                    current_tokens.append(token)
                    current_ner_tags.append(label)
                    current_nested_ner_tags.append(nested_label)
                else:
                    # New sentence
                    if not current_tokens:
                        # Consecutive empty lines will cause empty sentences
                        continue
                    assert len(current_tokens) == len(current_ner_tags), "💔 between len of tokens & labels"
                    assert len(current_ner_tags) == len(
                        current_nested_ner_tags
                    ), "💔 between len of labels & nested labels"
                    assert current_source, "💥 Source for new sentence was not set"
                    sentence = (
                        sentence_counter,
                        {
                            "id": str(sentence_counter),
                            "tokens": current_tokens,
                            "ner_tags": current_ner_tags,
                            "nested_ner_tags": current_nested_ner_tags,
                            "source": current_source,
                        },
                    )
                    sentence_counter += 1
                    current_tokens = []
                    current_ner_tags = []
                    current_nested_ner_tags = []
                    current_source = ""
                    yield sentence
            # Don't forget last sentence in dataset 🧐
            yield sentence_counter, {
                "id": str(sentence_counter),
                "tokens": current_tokens,
                "ner_tags": current_ner_tags,
                "nested_ner_tags": current_nested_ner_tags,
                "source": current_source,
            }