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Update files from the datasets library (from 1.2.0)

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

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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ annotations_creators:
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+ - crowdsourced
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+ language_creators:
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+ - expert-generated
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+ languages:
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+ - en
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+ - yo
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+ licenses:
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+ - unknown
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+ multilinguality:
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+ - multilingual
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+ size_categories:
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+ - n<1K
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+ source_datasets:
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+ - original
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+ task_categories:
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+ - text-scoring
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+ task_ids:
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+ - semantic-similarity-scoring
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+ ---
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+
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+ # Dataset Card for wordsim-353 in Yorùbá (yoruba_wordsim353)
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+
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+ ## Table of Contents
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks](#supported-tasks-and-leaderboards)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-instances)
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+ - [Data Splits](#data-instances)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
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+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Social Impact of Dataset](#social-impact-of-dataset)
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+ - [Discussion of Biases](#discussion-of-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** -
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+ - **Repository:** https://github.com/ajesujoba/YorubaTwi-Embedding
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+ - **Paper:** https://www.aclweb.org/anthology/2020.lrec-1.335/
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+ - **Leaderboard:** -
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+ - **Point of Contact:** Jesujoba Alabi ( jesujobaoluwadara.alabi (at) dfki.de ) and David Adelani ( didelani (at) lsv.uni-saarland.de )
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+
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+ ### Dataset Summary
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+
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+ A translation of the word pair similarity dataset wordsim-353 to Yorùbá.
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+
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+ ### Supported Tasks and Leaderboards
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+
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+ [More Information Needed]
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+
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+ ### Languages
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+
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+ Yorùbá (ISO 639-1: yo)
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ An instance consists of a pair of words as well as their similarity. The dataset contains both the original English words (from wordsim-353) as well as their translation to Yorùbá.
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+
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+ ### Data Fields
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+
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+ - `english1`: the first word of the pair; the original English word
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+ - `english2`: the second word of the pair; the original English word
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+ - `yoruba1`: the first word of the pair; translation to Yorùbá
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+ - `yoruba2`: the second word of the pair; translation to Yorùbá
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+ - `similarity`: similarity rating according to the English dataset
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+
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+ ### Data Splits
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+
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+ [More Information Needed]
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+
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+ ## Dataset Creation
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+
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+ ### Curation Rationale
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+
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+ [More Information Needed]
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+
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+ ### Source Data
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+
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+ #### Initial Data Collection and Normalization
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+
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+ [More Information Needed]
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+
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+ #### Who are the source language producers?
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+
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+ [More Information Needed]
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+
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+ ### Annotations
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+
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+ #### Annotation process
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+
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+ [More Information Needed]
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+
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+ #### Who are the annotators?
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+
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+ [More Information Needed]
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+
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+ ### Personal and Sensitive Information
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+
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+ [More Information Needed]
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+
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+ ## Considerations for Using the Data
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+
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+ ### Social Impact of Dataset
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+
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+ [More Information Needed]
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+
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+ ### Discussion of Biases
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+
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+ [More Information Needed]
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+
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+ ### Other Known Limitations
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+
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+ [More Information Needed]
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+
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+ ## Additional Information
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+
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+ ### Dataset Curators
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+
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+ [More Information Needed]
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+
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+ ### Licensing Information
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+
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+ [More Information Needed]
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+
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+ ### Citation Information
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+
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+ [More Information Needed]
dataset_infos.json ADDED
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+ {"default": {"description": "A translation of the word pair similarity dataset wordsim-353 to Yor\u00f9b\u00e1.\n\nThe dataset was presented in the paper\nAlabi et al.: Massive vs. Curated Embeddings for Low-Resourced\nLanguages: the Case of Yor\u00f9b\u00e1 and Twi (LREC 2020).\n", "citation": "@inproceedings{alabi-etal-2020-massive,\n title = \"Massive vs. Curated Embeddings for Low-Resourced Languages: the Case of {Y}or{\\`u}b{\\'a} and {T}wi\",\n author = \"Alabi, Jesujoba and\n Amponsah-Kaakyire, Kwabena and\n Adelani, David and\n Espa{\\~n}a-Bonet, Cristina\",\n booktitle = \"Proceedings of the 12th Language Resources and Evaluation Conference\",\n month = may,\n year = \"2020\",\n address = \"Marseille, France\",\n publisher = \"European Language Resources Association\",\n url = \"https://www.aclweb.org/anthology/2020.lrec-1.335\",\n pages = \"2754--2762\",\n language = \"English\",\n ISBN = \"979-10-95546-34-4\",\n}\n", "homepage": "https://github.com/ajesujoba/YorubaTwi-Embedding", "license": "", "features": {"english1": {"dtype": "string", "id": null, "_type": "Value"}, "english2": {"dtype": "string", "id": null, "_type": "Value"}, "yoruba1": {"dtype": "string", "id": null, "_type": "Value"}, "yoruba2": {"dtype": "string", "id": null, "_type": "Value"}, "similarity": {"dtype": "float32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "yoruba_wordsim353", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 19299, "num_examples": 353, "dataset_name": "yoruba_wordsim353"}}, "download_checksums": {"https://raw.githubusercontent.com/ajesujoba/YorubaTwi-Embedding/master/Yoruba/wordSim353_yo.csv": {"num_bytes": 17039, "checksum": "e0b14d7c8cfa8b08808862f008124bd0314a33e401951007faf3563ed8ff13f5"}}, "download_size": 17039, "post_processing_size": null, "dataset_size": 19299, "size_in_bytes": 36338}}
dummy/0.0.0/dummy_data.zip ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:7a0a19435b7495abb0bf7b2e7f46dccf2139ad0331b1238443e5c21c69691f47
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+ size 418
yoruba_wordsim353.py ADDED
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+ # coding=utf-8
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+ # Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
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+ # You may obtain a copy of the License at
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+ #
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+ # http://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+
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+ # Lint as: python3
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+ """WordSim-353 for Yoruba"""
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+
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+ from __future__ import absolute_import, division, print_function
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+
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+ import csv
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+
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+ import datasets
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+
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+
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+ _DESCRIPTION = """\
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+ A translation of the word pair similarity dataset wordsim-353 to Yorùbá.
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+
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+ The dataset was presented in the paper
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+ Alabi et al.: Massive vs. Curated Embeddings for Low-Resourced
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+ Languages: the Case of Yorùbá and Twi (LREC 2020).
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+ """
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+
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+ _CITATION = """\
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+ @inproceedings{alabi-etal-2020-massive,
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+ title = "Massive vs. Curated Embeddings for Low-Resourced Languages: the Case of {Y}or{\\`u}b{\\'a} and {T}wi",
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+ author = "Alabi, Jesujoba and
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+ Amponsah-Kaakyire, Kwabena and
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+ Adelani, David and
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+ Espa{\\~n}a-Bonet, Cristina",
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+ booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
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+ month = may,
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+ year = "2020",
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+ address = "Marseille, France",
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+ publisher = "European Language Resources Association",
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+ url = "https://www.aclweb.org/anthology/2020.lrec-1.335",
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+ pages = "2754--2762",
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+ language = "English",
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+ ISBN = "979-10-95546-34-4",
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+ }
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+ """
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+
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+ _DOWNLOAD_URL = "https://raw.githubusercontent.com/ajesujoba/YorubaTwi-Embedding/master/Yoruba/wordSim353_yo.csv"
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+
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+
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+ class YorubaWordsim353(datasets.GeneratorBasedBuilder):
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+ """WordSim-353 for Yoruba."""
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+
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+ def _info(self):
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=datasets.Features(
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+ {
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+ "english1": datasets.Value("string"),
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+ "english2": datasets.Value("string"),
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+ "yoruba1": datasets.Value("string"),
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+ "yoruba2": datasets.Value("string"),
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+ "similarity": datasets.Value("float32"),
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+ }
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+ ),
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+ homepage="https://github.com/ajesujoba/YorubaTwi-Embedding",
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ test_path = dl_manager.download_and_extract(_DOWNLOAD_URL)
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+ return [
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+ datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
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+ ]
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+
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+ def _generate_examples(self, filepath):
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+ """Generate WordSim-353 for Yoruba examples."""
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+ with open(filepath, encoding="utf-8") as csv_file:
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+ csv_reader = csv.DictReader(csv_file, delimiter=",")
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+ for id_, row in enumerate(csv_reader):
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+ yield id_, {
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+ "english1": row["English1"],
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+ "english2": row["English2"],
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+ "yoruba1": row["Yoruba1"],
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+ "yoruba2": row["Yoruba2"],
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+ "similarity": row["EngSim"],
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+ }