chore: add WSD dataset

.gitattributes

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+*tfevents* filter=lfs diff=lfs merge=lfs -text
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+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+annotations_creators:
+- expert-generated
+language:
+- pl
+language_creators:
+- expert-generated
+- found
+license:
+- cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: wsd-polish-datasets
+size_categories:
+- 1M<n<10M
+source_datasets:
+- original
+tags: []
+task_categories:
+- token-classification
+task_ids:
+- word-sense-disambiguation
+---
+# Word Sense Disambiguation Corpora for Polish
+
+## 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:** https://link.springer.com/chapter/10.1007/978-3-031-08754-7_70
+- **Point of Contact:** [email protected], [email protected]
+
+### Dataset Summary
+
+`WSD Polish Datasets` are comprehensive benchmark for word sense disambiguation (WSD) classification task written in low-resource language Polish.
+It consists of 6 distinct datasets, manually annotated based on plWordNet-4.2:
+- KPWr
+- KPWr-100
+- Sherlock (SPEC)
+- Skladnica
+- WikiGlex
+- EmoGlex
+- Walenty
+
+
+### Supported Tasks and Leaderboards
+
+Word sense disambiguation task
+
+### Languages
+
+Polish language, PL
+
+## Dataset Structure
+
+### Data Instances
+
+Data are structured in JSONL format, each single text sample is divided by sentence.
+
+```
+{
+  "text": "Wpierw pani Hudson została zerwana z łóżka, po czym odegrała się na mnie, a ja - na tobie.",
+  "tokens": [
+    {
+      "index": 0,
+      "position": [
+        0,
+        6
+      ],
+      "orth": "Wpierw",
+      "lemma": "wpierw",
+      "pos": "adv",
+      "ctag": "adv"
+    },
+    {
+      "index": 1,
+      "position": [
+        7,
+        11
+      ],
+      "orth": "pani",
+      "lemma": "pani",
+      "pos": "noun",
+      "ctag": "subst:nom:f:sg"
+    },
+    {
+      "index": 2,
+      "position": [
+        12,
+        18
+      ],
+      "orth": "Hudson",
+      "lemma": "Hudson",
+      "pos": "noun",
+      "ctag": "subst:nom:f:sg"
+    },
+    {
+      "index": 3,
+      "position": [
+        19,
+        26
+      ],
+      "orth": "została",
+      "lemma": "zostać",
+      "pos": "verb",
+      "ctag": "praet:perf:f:sg"
+    },
+    {
+      "index": 4,
+      "position": [
+        27,
+        34
+      ],
+      "orth": "zerwana",
+      "lemma": "zerwać",
+      "pos": "verb",
+      "ctag": "ppas:perf:nom:f:aff:sg"
+    },
+    {
+      "index": 5,
+      "position": [
+        35,
+        36
+      ],
+      "orth": "z",
+      "lemma": "z",
+      "pos": "prep",
+      "ctag": "prep:gen:nwok"
+    },
+    {
+      "index": 6,
+      "position": [
+        37,
+        42
+      ],
+      "orth": "łóżka",
+      "lemma": "łóżko",
+      "pos": "noun",
+      "ctag": "subst:gen:n:sg"
+    },
+    {
+      "index": 7,
+      "position": [
+        42,
+        43
+      ],
+      "orth": ",",
+      "lemma": ",",
+      "pos": "interp",
+      "ctag": "interp"
+    },
+   ...
+  ],
+  "phrases": [
+    {
+      "token_indices": [
+        10,
+        11
+      ],
+      "head": 10,
+      "lemma": "odegrać się"
+    }
+  ],
+  "wsd": [
+    {
+      "token_id": 0,
+      "pl_sense": "najpierw.1.r",
+      "plWN_syn_id": "477654",
+      "plWN_lex_id": "718453",
+      "plWN_syn_id_new": "98ee84eb5f4611eda4930242ac130002",
+      "plWN_lex_id_new": "8c5acff25f4611eda4930242ac130002"
+    },
+    {
+      "token_id": 1,
+      "pl_sense": "niewiasta.1.n",
+      "plWN_syn_id": "129",
+      "plWN_lex_id": "4345",
+      "plWN_syn_id_new": "8e384db65f4611eda4930242ac130002",
+      "plWN_lex_id_new": "71c622355f4611eda4930242ac130002"
+    },
+    {
+      "token_id": 3,
+      "pl_sense": "zostać.6.v",
+      "plWN_syn_id": "7068800",
+      "plWN_lex_id": "7069137",
+      "plWN_syn_id_new": "9924a0215f4611eda4930242ac130002",
+      "plWN_lex_id_new": "8cfcc4395f4611eda4930242ac130002"
+    },
+    {
+      "token_id": 4,
+      "pl_sense": "zerwać.9.v",
+      "plWN_syn_id": "81101",
+      "plWN_lex_id": "81717",
+      "plWN_syn_id_new": "8fec998d5f4611eda4930242ac130002",
+      "plWN_lex_id_new": "754169415f4611eda4930242ac130002"
+    },
+    {
+      "token_id": 6,
+      "pl_sense": "łoże.1.n",
+      "plWN_syn_id": "7419",
+      "plWN_lex_id": "12010",
+      "plWN_syn_id_new": "8e88576c5f4611eda4930242ac130002",
+      "plWN_lex_id_new": "71f360dd5f4611eda4930242ac130002"
+    },
+    {
+      "token_id": 10,
+      "pl_sense": "zemścić_się.1.v",
+      "plWN_syn_id": "62160",
+      "plWN_lex_id": "88109",
+      "plWN_syn_id_new": "8fbbdfff5f4611eda4930242ac130002",
+      "plWN_lex_id_new": "7568f5085f4611eda4930242ac130002"
+    }
+  ]
+}
+```
+
+### Data Fields
+
+Description of json keys:
+- `text`: text of the sentence
+- `tokens`: list of tokens made by tokenization process
+  - `index`: token order index in sentence
+  - `position`: token chars span indices <included, excluded>
+  - `orth`: word
+  - `lemma`: lemmatised word
+  - `pos`: part of speech
+  - `ctag`: morphosyntactic tag
+- `phrases`: list of multi-word 
+- `wsd`: annotation labels for the WSD task
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### 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
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+````
+@InProceedings{10.1007/978-3-031-08754-7_70,
+  author="Janz, Arkadiusz
+  and Dziob, Agnieszka
+  and Oleksy, Marcin
+  and Baran, Joanna",
+  editor="Groen, Derek
+  and de Mulatier, Cl{\'e}lia
+  and Paszynski, Maciej
+  and Krzhizhanovskaya, Valeria V.
+  and Dongarra, Jack J.
+  and Sloot, Peter M. A.",
+  title="A Unified Sense Inventory for Word Sense Disambiguation in Polish",
+  booktitle="Computational Science -- ICCS 2022",
+  year="2022",
+  publisher="Springer International Publishing",
+  address="Cham",
+  pages="682--689",
+  isbn="978-3-031-08754-7"
+}
+````

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wsd_polish_datasets.py

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+# 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 itertools
+import json
+from typing import Sequence
+
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+
+_CITATION = """\
+@InProceedings{10.1007/978-3-031-08754-7_70,
+  author="Janz, Arkadiusz
+  and Dziob, Agnieszka
+  and Oleksy, Marcin
+  and Baran, Joanna",
+  editor="Groen, Derek
+  and de Mulatier, Cl{\'e}lia
+  and Paszynski, Maciej
+  and Krzhizhanovskaya, Valeria V.
+  and Dongarra, Jack J.
+  and Sloot, Peter M. A.",
+  title="A Unified Sense Inventory for Word Sense Disambiguation in Polish",
+  booktitle="Computational Science -- ICCS 2022",
+  year="2022",
+  publisher="Springer International Publishing",
+  address="Cham",
+  pages="682--689",
+  isbn="978-3-031-08754-7"
+}
+"""
+_DESCRIPTION = """\
+Polish WSD training data manually annotated by experts according to plWordNet-4.2.
+"""
+
+_LICENSE = "cc-by-4.0"
+
+_BASE_URL = "https://huggingface.co/datasets/clarin-knext/wsd_polish_datasets/resolve/main/data/"
+
+_CORPUS_NAMES = [
+    "sherlock",
+    "skladnica",
+    "wikiglex",
+    "emoglex",
+    "walenty",
+    "kpwr",
+    "kpwr-100",
+]
+
+_DATA_TYPES = [
+    "sentence",
+    "text",
+]
+
+_URLS = {
+    "text": {corpus: f"{_BASE_URL}{corpus}_text.jsonl" for corpus in _CORPUS_NAMES},
+    "sentence": {
+        corpus: f"{_BASE_URL}{corpus}_sentences.jsonl" for corpus in _CORPUS_NAMES
+    },
+}
+
+
+class WsdPolishBuilderConfig(datasets.BuilderConfig):
+    def __init__(
+        self,
+        data_urls: Sequence[str],
+        corpus: str,
+        data_type: str,
+        **kwargs,
+    ):
+        super(WsdPolishBuilderConfig, self).__init__(
+            name=f"{corpus}_{data_type}",
+            version=datasets.Version("1.0.0"),
+            **kwargs,
+        )
+
+        self.data_type = data_type
+        self.corpus = corpus
+        self.data_urls = data_urls
+        if self.data_type not in _DATA_TYPES:
+            raise ValueError(
+                f"Corpus type {self.data_type} is not supported. Enter one of: {_DATA_TYPES}"
+            )
+        if self.corpus not in (*_CORPUS_NAMES, "all"):
+            raise ValueError(
+                f"Corpus name `{self.corpus}` is not available. Enter one of: {(*_CORPUS_NAMES, 'all')}"
+            )
+
+
+class WsdPolishDataset(datasets.GeneratorBasedBuilder):
+    """Polish WSD training data"""
+
+    BUILDER_CONFIGS = [
+        WsdPolishBuilderConfig(
+            corpus=corpus_name,
+            data_type=data_type,
+            data_urls=[_URLS[data_type][corpus_name]],
+            description=f"Data part covering `{corpus_name}` corpora in `{data_type}` segmentation.",
+        )
+        for corpus_name, data_type in itertools.product(_CORPUS_NAMES, _DATA_TYPES)
+    ]
+    BUILDER_CONFIGS.extend(
+        [
+            WsdPolishBuilderConfig(
+                corpus="all",
+                data_type=data_type,
+                data_urls=_URLS[data_type].copy().values(),
+                description=f"Data part covering `all` corpora in `{data_type}` segmentation.",
+            )
+            for data_type in _DATA_TYPES
+        ]
+    )
+
+    DEFAULT_CONFIG_NAME = "skladnica_text"
+
+    def _info(self) -> datasets.DatasetInfo:
+        text_features = {
+            "text": datasets.Value("string"),
+            "tokens": datasets.features.Sequence(
+                dict(
+                    {
+                        "position": datasets.features.Sequence(
+                            length=2,
+                            feature=datasets.Value("int32"),
+                        ),
+                        "orth": datasets.Value("string"),
+                        "lemma": datasets.Value("string"),
+                    }
+                ),
+            ),
+            "phrases": datasets.features.Sequence(
+                dict(
+                    {
+                        "indices": datasets.features.Sequence(
+                            feature=datasets.Value("int32")
+                        ),
+                        "head": datasets.Value("int32"),
+                        "lemma": datasets.Value("string"),
+                    }
+                ),
+            ),
+            "wsd": datasets.features.Sequence(
+                dict(
+                    {
+                        "index": datasets.Value("int32"),
+                        "plWN_syn_id": datasets.Value("string"),
+                        "plWN_lex_id": datasets.Value("string"),
+                    }
+                ),
+            ),
+        }
+        if self.config.data_type == "sentence":
+            features = datasets.Features(
+                {
+                    "sentences": datasets.features.Sequence(text_features),
+                }
+            )
+        else:
+            features = datasets.Features(text_features)
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        filepaths = dl_manager.download_and_extract(self.config.data_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepaths": filepaths,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepaths: Sequence[str]):
+        key_iter = 0
+        for filepath in filepaths:
+            with open(filepath, encoding="utf-8") as f:
+                for data in (json.loads(line) for line in f):
+                    if self.config.data_type == "sentence":
+                        yield key_iter, {
+                            "sentences": [
+                                self._process_example(sent)
+                                for sent in data["sentences"]
+                            ]
+                        }
+                    else:
+                        data.pop("context_file")
+                        yield key_iter, self._process_example(data)
+
+                    key_iter += 1
+
+    @staticmethod
+    def _process_example(data: dict) -> dict:
+        return {
+            "text": data["text"],
+            "tokens": [
+                {
+                    "position": tok["position"],
+                    "orth": tok["orth"],
+                    "lemma": tok["lemma"],
+                }
+                for tok in data["tokens"]
+            ],
+            "wsd": [
+                {
+                    "index": tok["index"],
+                    "plWN_syn_id": tok["plWN_syn_id"],
+                    "plWN_lex_id": tok["plWN_lex_id"],
+                }
+                for tok in data["wsd"]
+            ],
+            "phrases": [
+                {
+                    "indices": tok["indices"],
+                    "head": tok["head"],
+                    "lemma": tok["lemma"],
+                }
+                for tok in data["phrases"]
+            ],
+        }