Update files from the datasets library (from 1.2.0)

Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- found
+languages:
+- sv
+licenses:
+- cc-by-4-0
+multilinguality:
+- monolingual
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- structure-prediction
+task_ids:
+- named-entity-recognition
+---
+
+# Swedish NER Corpus
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-instances)
+  - [Data Splits](#data-instances)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+
+## Dataset Description
+
+- **Homepage:** [https://github.com/klintan/swedish-ner-corpus]()
+- **Repository:** [https://github.com/klintan/swedish-ner-corpus]()
+- **Point of contact:** Andreas Klintberg (ankl@kth.se)
+
+### Dataset Summary
+
+Webbnyheter 2012 from Spraakbanken, semi-manually annotated and adapted for CoreNLP Swedish NER. Semi-manually defined in this case as: Bootstrapped from Swedish Gazetters then manually correcte/reviewed by two independent native speaking swedish annotators. No annotator agreement calculated.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+Swedish
+
+## Dataset Structure
+
+### Data Instances
+
+A sample dataset instance is provided below:
+
+```json
+{'id': '3',
+ 'ner_tags': [4, 4, 0, 0, 0, 0, 0, 0, 3, 3, 0],
+ 'tokens': ['Margaretha',
+  'Fahlgren',
+  ',',
+  'professor',
+  'i',
+  'litteraturvetenskap',
+  ',',
+  'vice-rektor',
+  'Uppsala',
+  'universitet',
+  '.']}
+```
+
+
+
+### Data Fields
+
+- `id`: id of the sentence
+- `token`: current token
+- `ner_tag`: ner tag of the token
+
+Full fields:
+
+```json
+{
+  "id":{
+    "feature_type":"Value"
+      "dtype":"string"
+      }
+      "tokens":{
+        "feature_type":"Sequence"
+        "feature":{
+        "feature_type":"Value"
+        "dtype":"string"
+        }
+      }
+    "ner_tags":{
+      "feature_type":"Sequence"
+        "dtype":"int32"
+        "feature":{
+        "feature_type":"ClassLabel"
+          "dtype":"int32"
+          "class_names":[
+              0:"0"
+              1:"LOC"
+              2:"MISC"
+              3:"ORG"
+              4:"PER"
+              ]
+      }
+  }
+}
+```
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+[More Information Needed]
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+[More Information Needed]
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+The original dataset was provided by Språkbanken which consists of news from Swedish newspapers' websites.
+
+### Licensing Information
+
+https://github.com/klintan/swedish-ner-corpus/blob/master/LICENSE
+
+### Citation Information
+
+[More Information Needed]

dataset_infos.json

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+{"default": {"description": "    Webbnyheter 2012 from Spraakbanken, semi-manually annotated and adapted for CoreNLP Swedish NER. Semi-manually defined in this case as: Bootstrapped from Swedish Gazetters then manually correcte/reviewed by two independent native speaking swedish annotators. No annotator agreement calculated.\n", "citation": "", "homepage": "https://github.com/klintan/swedish-ner-corpus", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 5, "names": ["0", "LOC", "MISC", "ORG", "PER"], "names_file": null, "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "swedish_ner_corpus_dataset", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2032630, "num_examples": 6886, "dataset_name": "swedish_ner_corpus_dataset"}, "test": {"name": "test", "num_bytes": 755234, "num_examples": 2453, "dataset_name": "swedish_ner_corpus_dataset"}}, "download_checksums": {"https://raw.githubusercontent.com/klintan/swedish-ner-corpus/master/train_corpus.txt": {"num_bytes": 986349, "checksum": "b0ba93840c13b882a336f5ae3b4af4cc5238203cd504acd5f44d8a7f643abf9f"}, "https://raw.githubusercontent.com/klintan/swedish-ner-corpus/master/test_corpus.txt": {"num_bytes": 398209, "checksum": "b13c8626cf6478df4b3e9a2e7fa5276fd45f757bc5af9f6bc4abc7d789af2fdd"}}, "download_size": 1384558, "post_processing_size": null, "dataset_size": 2787864, "size_in_bytes": 4172422}}

dummy/1.0.0/dummy_data.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b78ed0de3025ccdcad974b048802b521128d8831d0d55b8ce6e844ccc69d9c5e
+size 450

swedish_ner_corpus.py

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+# 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
+import datasets
+
+
+_DESCRIPTION = """\
+Webbnyheter 2012 from Spraakbanken, semi-manually annotated and adapted for CoreNLP Swedish NER. Semi-manually defined in this case as: Bootstrapped from Swedish Gazetters then manually correcte/reviewed by two independent native speaking swedish annotators. No annotator agreement calculated.
+"""
+_HOMEPAGE_URL = "https://github.com/klintan/swedish-ner-corpus"
+_TRAIN_URL = "https://raw.githubusercontent.com/klintan/swedish-ner-corpus/master/train_corpus.txt"
+_TEST_URL = "https://raw.githubusercontent.com/klintan/swedish-ner-corpus/master/test_corpus.txt"
+_CITATION = None
+
+
+class SwedishNERCorpus(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "id": datasets.Value("string"),
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(names=["0", "LOC", "MISC", "ORG", "PER"])
+                    ),
+                },
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE_URL,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        train_path = dl_manager.download_and_extract(_TRAIN_URL)
+        test_path = dl_manager.download_and_extract(_TEST_URL)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"datapath": train_path},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"datapath": test_path},
+            ),
+        ]
+
+    def _generate_examples(self, datapath):
+        sentence_counter = 0
+        with open(datapath, encoding="utf-8") as f:
+            current_words = []
+            current_labels = []
+            for row in f:
+                row = row.rstrip()
+                row_split = row.split()
+                if len(row_split) == 2:
+                    token, label = row_split
+                    current_words.append(token)
+                    current_labels.append(label)
+                else:
+                    if not current_words:
+                        continue
+                    assert len(current_words) == len(current_labels), "word len doesnt match label length"
+                    sentence = (
+                        sentence_counter,
+                        {
+                            "id": str(sentence_counter),
+                            "tokens": current_words,
+                            "ner_tags": current_labels,
+                        },
+                    )
+                    sentence_counter += 1
+                    current_words = []
+                    current_labels = []
+                    yield sentence
+
+            # if something remains:
+            if current_words:
+                sentence = (
+                    sentence_counter,
+                    {
+                        "id": str(sentence_counter),
+                        "tokens": current_words,
+                        "ner_tags": current_labels,
+                    },
+                )
+                yield sentence