Hennig, "The Spoken Wikipedia corpus collection: Harvesting, alignment and an application to hyperlistening," Language Resources and Evaluation, 2018, special issue representing significant contributions of LREC 2016. [Online]. Available: http://dx.doi.org/10.1007/s10579-017-9410-y...
Japanese-Wikipedia Wikification Corpus SummaryA Wikipedia tagged corpus specific to creating a machine learning model for Wikification which stands for the process of linking terms in a plain text to corresponding Wikipedia entities.DownloadDue to the large file size, files are uploaded to Dropbox....
titles: a text file containing a list of titles for each article in whih a story plot was found and extracted. Using the code to recreate the corpus I have also included the Python script used to extract the story plots. wikiPlots.py requires: An English Wikipedia dump Wikiextractor The Be...
Source File: gen_corpus.py From Living-Audio-Dataset with Apache License 2.0 6 votes def main(): parser = argparse.ArgumentParser() parser.add_argument("-n", "--max-no-articles", type = int, default=10, help = "maximum number of articles to download") parser.add_argument("-w", ...
Preparing the corpus First, download the dump of all Wikipedia articles from http://download.wikimedia.org/enwiki/ (you want the file enwiki-latest-pages-articles.xml.bz2, or enwiki-YYYYMMDD-pages-articles.xml.bz2 for date-specific dumps). This file is about 8GB in size and contains (a ...
using a carefully curated corpus of English Wikipedia claims and their current citations, we train (1) a retriever component that converts claims and contexts into symbolic and neural search queries optimized to find candidate citations in a web-scale corpus; and (2) a verification model that ...
I discuss how the data are subjected to moves analysis on the one hand and a corpus linguistic examination on the other. The remainder of the chapter is dedicated to presenting key findings of the moves analysis. This discussion of findings reaches from the identification of the overarching threa...
Sure, the dataset is big (180GB for the English corpus), but that’s not the obstacle per se. We’ve been able to build full-text indexes on larger datasets for a long time. The obstacle is that until now, off-the-shelf vector databases could not index a dataset larger than memory...
Wikipedia Entity Vectors[1] is a distributed representation of words and named entities (NEs). The words and NEs are mapped to the same vector space. The vectors are trained with skip-gram algorithm using preprocessed Wikipedia text as the corpus. ...
An output file saved in text word2vec format.entities.tsvA tsv file containing terms appeared in a plain text and corresponding Wikipedia entities. More details are described in Japanese-Wikipedia Wikification Corpus.version.ymlA YAML-formatted file to store version information for referred dictionary...