Datasets:
annotations_creators:
- expert-generated
language_creators:
- expert-generated
languages:
- en
licenses:
- unknown
multilinguality:
- monolingual
pretty_name: slp3ed-iknlp2022
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
- text-retrieval
- summarization
- question-generation
Dataset Card for IK-NLP-22 Speech and Language Processing
Table of Contents
Dataset Description
- Source: Stanford
- Point of Contact: Gabriele Sarti
Dataset Summary
This dataset contains chapters extracted from the Speech and Language Processing book (3ed) by Jurafsky and Martin via a semi-automatic procedure (see below for additional details). Moreover, a small set of conceptual questions associated with each chapter is provided alongside possible answers.
Only the content of chapters 2 to 11 of the book draft are provided, since these are the ones relevant to the contents of the 2022 edition of the Natural Language Processing course at the Information Science Master's Degree (IK) at the University of Groningen, taught by Arianna Bisazza with the assistance of Gabriele Sarti.
The Speech and Language Processing book was made freely available by the authors Dan Jurafsky and James H. Martin on the Stanford University website. The present dataset was created for educational purposes, and is based on the draft of the 3rd edition of the book accessed on December 29th, 2021. All rights of the present contents are attributed to the original authors.
Projects
To be provided.
Languages
The language data of Speech and Language Processing is in English (BCP-47 en)
Dataset Structure
Data Instances
The dataset contains two configurations: paragraphs (default) and questions.
Paragraphs Configuration
The paragraphs configuration contains all the paragraphs of the selected book chapters, each associated with the respective chapter, section and subsection. An example from the train split of the paragraphs config is provided below. The example belongs to section 2.3 but not to a subsection, so the n_subsection and subsection fields are empty strings.
{
"n_chapter": "2",
"chapter": "Regular Expressions",
"n_section": "2.3",
"section": "Corpora",
"n_subsection": "",
"subsection": "",
"text": "It's also quite common for speakers or writers to use multiple languages in a single communicative act, a phenomenon called code switching. Code switching (2.2) Por primera vez veo a @username actually being hateful! it was beautiful:)"
}
The text is provided as-is, without further preprocessing or tokenization.
Questions Configuration
To be completed.
Data Splits
| config | train | test |
|---|---|---|
paragraphs |
1722 | - |
questions |
TBD | TBD |
Dataset Creation
The contents of the Speech and Language Processing book PDF were extracted using the PDF to S2ORC JSON Converter by AllenAI. The texts extracted by the converter were then manually cleaned to remove end-of-chapter exercises and other irrelevant content (e.g. tables, TikZ figures, etc.). Some issues in the parsed content were preserved in the final version to maintain a naturalistic setting for the associated projects, promoting the use of data filtering heuristics for students.
Additional Information
Dataset Curators
For problems on this 🤗 Datasets version, please contact us at ik-nlp-course@rug.nl.
Licensing Information
Please refer to the authors' websites for licensing information.
Citation Information
Please cite the authors if you use these corpora in your work:
@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}
}