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README.md

@@ -8,4 +8,135 @@ language:
 pretty_name: Natural Language Inference datasets
 size_categories:
 - 1K<n<10K
----
+---
+
+# Natural Language Inference datasets
+
+## Table of Contents
+
+- [Dataset Description](#dataset-description)
+    - [Dataset Summary](#dataset-summary)
+    - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+    - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+    - [Data Instances](#data-instances)
+    - [Data Fields](#data-fields)
+    - [Data Splits](#data-splits)
+- [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)
+    - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:**
+- **Repository:**
+- **Paper:**
+- **Point of Contact:** [email protected]
+
+### Dataset Summary
+
+Collection of sentence pairs annotated for the Natural Language Inference (NLI) task.
+It consists of 2 distinct datasets:
+
+- SNLI
+- WNLI
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+Polish language, PL
+English language, EN
+
+## Dataset Structure
+
+### Data Instances
+
+Data are structured in JSONL format, each sample consists of sentence pair with a label.
+
+```
+{
+  "id": 0, 
+  "sentence_1": "The tourist is wandering on the beach.", 
+  "sentence_2": "The tourist crosses the forest stream.", 
+  "label": "contradiction"
+}
+```
+
+### Data Fields
+
+Description of json keys:
+
+- `id`: identifier of the sentence pair
+- `sentence_1`: first sentence
+- `sentence_2`: second sentence
+- `label`: NLI annotation
+- `origin_label`: original annotation for Stanford NLI data (only in SNLI config)
+
+### Data Splits
+
+We do not specify an exact data split for training and evaluation.
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection, Normalization and Post-processing
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+- professional linguists (mention all people involved)
+
+### Personal and Sensitive Information
+
+The datasets do not contain any personal or sensitive information.
+
+## Considerations for Using the Data
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+Arkadiusz Janz ([email protected])
+
+### Licensing Information
+
+SNLI [CC-BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)  
+WNLI [CC-BY-SA 4.0](https://creativecommons.org/licenses/by-sa/4.0/)
+
+### Citation Information
+
+[More Information Needed]

data/snli_nli_en.jsonl

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nli_datasets.py

@@ -0,0 +1,108 @@
+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# 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.
+import json
+
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+_DESCRIPTION = """\
+Data for NLI task annotated manually
+"""
+
+_BASE_URL = "https://huggingface.co/datasets/clarin-knext/nli_datasets/resolve/main/data/"
+
+_DATASET_NAME = [
+    "snli_pl",
+    "snli_en",
+    "wnli_pl",
+    "wnli_en",
+]
+
+_URLS = {
+    f"{dataset}_{lang}": f"{_BASE_URL}{dataset}_nli_{lang}.jsonl"
+    for dataset, lang in (dataset_name.split('_') for dataset_name in _DATASET_NAME)
+}
+
+
+class NLIDatasetBuilderConfig(datasets.BuilderConfig):
+    def __init__(
+        self,
+        data_url: str,
+        name: str,
+        **kwargs,
+    ):
+        super(NLIDatasetBuilderConfig, self).__init__(
+            name=name,
+            version=datasets.Version("1.0.0"),
+            **kwargs,
+        )
+
+        self.name = name
+        self.data_url = data_url
+        if self.name not in _DATASET_NAME:
+            raise ValueError(
+                f"Config name `{self.name}` is not available. Enter one of: {_DATASET_NAME}"
+            )
+
+
+class NLIDataset(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        NLIDatasetBuilderConfig(
+            name=dataset,
+            data_url=_URLS[dataset],
+            description=f"Dataset {dataset} with NLI annotation.",
+        )
+        for dataset in _DATASET_NAME
+    ]
+
+    DEFAULT_CONFIG_NAME = "wnli_en"
+
+    def _info(self) -> datasets.DatasetInfo:
+        features = {
+            "id": datasets.Value("int32"),
+            "sentence_1": datasets.Value("string"),
+            "sentence_2": datasets.Value("string"),
+            "label": datasets.Value("string"),
+        }
+
+        if self.config.name.startswith('snli'):
+            features["origin_label"] = datasets.Value("string")
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(features),
+            supervised_keys=None,
+            # license=_LICENSE,
+            # citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        filepath = dl_manager.download_and_extract(self.config.data_url)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": filepath,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath: str):
+        key_iter = 0
+        with open(filepath, encoding="utf-8") as f:
+            for data in (json.loads(line) for line in f):
+                yield key_iter, data
+                key_iter += 1