Datasets:
Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
License:
| import csv | |
| import sys | |
| import datasets | |
| import pandas as pd | |
| from typing import List | |
| csv.field_size_limit(sys.maxsize) | |
| _CITATION = """\ | |
| @book{slp3ed-iknlp2022, | |
| author = {Jurafsky, Daniel and Martin, James}, | |
| year = {2021}, | |
| month = {12}, | |
| pages = {1--235, 1--19}, | |
| title = {Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition}, | |
| volume = {3} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| Paragraphs from the Speech and Language Processing book (3ed) by Jurafsky and Martin extracted semi-automatically | |
| from Chapters 2 to 11 of the original book draft. | |
| """ | |
| _HOMEPAGE = "https://www.rug.nl/masters/information-science/?lang=en" | |
| _LICENSE = "See https://web.stanford.edu/~jurafsky/slp3/" | |
| _PARAGRAPHS_URL = "https://huggingface.co/datasets/GroNLP/ik-nlp-22_slp/raw/main/slp3ed.csv" | |
| _QUESTIONS_URL = "https://huggingface.co/datasets/GroNLP/ik-nlp-22_slp/raw/main/slp_questions.csv" | |
| class IkNlp22SlpConfig(datasets.BuilderConfig): | |
| """BuilderConfig for IK NLP '22 Speech and Language Processing.""" | |
| def __init__( | |
| self, | |
| features, | |
| **kwargs, | |
| ): | |
| """ | |
| Args: | |
| features: `list[string]`, list of the features that will appear in the | |
| feature dict. Should not include "label". | |
| **kwargs: keyword arguments forwarded to super. | |
| """ | |
| super().__init__(version=datasets.Version("1.0.0"), **kwargs) | |
| self.features = features | |
| class IkNlp22Slp(datasets.GeneratorBasedBuilder): | |
| VERSION = datasets.Version("1.0.0") | |
| BUILDER_CONFIGS = [ | |
| IkNlp22SlpConfig( | |
| name="paragraphs", | |
| features=["n_chapter", "chapter", "n_section", "section", "n_subsection", "subsection", "text"], | |
| ), | |
| IkNlp22SlpConfig( | |
| name="questions", | |
| features=["chapter", "section", "subsection", "question", "paragraph", "answer"], | |
| ), | |
| ] | |
| DEFAULT_CONFIG_NAME = "paragraphs" | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features({feature: datasets.Value("string") for feature in self.config.features}), | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| if self.config.name == "paragraphs": | |
| paragraphs_file = dl_manager.download_and_extract(_PARAGRAPHS_URL) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": paragraphs_file, | |
| "features": self.config.features, | |
| }, | |
| ), | |
| ] | |
| else: | |
| pairs_file = dl_manager.download_and_extract(_QUESTIONS_URL) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": pairs_file, | |
| "features": self.config.features, | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath: str, features: List[str]): | |
| """Yields examples as (key, example) tuples.""" | |
| data = pd.read_csv(filepath) | |
| for id_, row in data.iterrows(): | |
| yield id_, row.to_dict() |