Work

Overview of AMALGUM - Large Silver Quality Annotations across English Genres

Year: 2021

Type: article

Abstract: Corpus resources for Linguistics and NLP research on discourse phenomena, such as coreference and discourse trees, are limited by a lack of large scale, well-understood, annotated datasets: corpora are either very large (100M-10G tokens) but shallowly annotated and with unknown composition, or richly annotated, but smaller. Here, we present a resource that takes a middle path, combining some of the best features of scraped corpora - size, open licenses, lexical diversity - and high quality curated data for more interpretable inferences with complex annotations.

Source: ScholarWorks@UMassAmherst (University of Massachusetts Amherst)

DOI: 10.7275/ep47-3t54

Authors: Gessler, Luke D., Peng, Siyao, Liu, Yang, Zhu, Yilun, Behzad, Shabnam, Zeldes, Amir

Institution: Georgetown University

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W3197065044

FWCI:

Cites: 7

Cited by: 1

Related to: 10