EEVEE: An Easy Annotation Tool for Natural Language Processing

Axel Sorensen; Siyao Peng; Barbara Plank; Rob Van Der Goot

EEVEE: An Easy Annotation Tool for Natural Language Processing

Axel Sorensen, Siyao Peng, Barbara Plank, Rob Van Der Goot

NLPnorth

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

Abstract

Annotation tools are the starting point for creating Natural Language Processing (NLP) datasets. There is a wide variety of tools available; setting up these tools is however a hindrance. We propose Eevee, an annotation tool focused on simplicity, efficiency, and ease of use. It can run directly in the browser (no setup required) and uses tab-separated files (as opposed to character offsets or task-specific formats) for annotation. It allows for annotation of multiple tasks on a single dataset and supports four task-types: sequence labeling, span labeling, text classification and seq2seq.

Original language	English
Title of host publication	Proceedings of The 18th Linguistic Annotation Workshop (LAW-XVIII)
Editors	Sophie Henning, Manfred Stede
Number of pages	6
Place of Publication	St. Julians, Malta
Publisher	Association for Computational Linguistics
Publication date	1 Mar 2024
Pages	216-221
Publication status	Published - 1 Mar 2024

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Cite this

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title = "EEVEE: An Easy Annotation Tool for Natural Language Processing",

abstract = "Annotation tools are the starting point for creating Natural Language Processing (NLP) datasets. There is a wide variety of tools available; setting up these tools is however a hindrance. We propose Eevee, an annotation tool focused on simplicity, efficiency, and ease of use. It can run directly in the browser (no setup required) and uses tab-separated files (as opposed to character offsets or task-specific formats) for annotation. It allows for annotation of multiple tasks on a single dataset and supports four task-types: sequence labeling, span labeling, text classification and seq2seq.",

author = "Axel Sorensen and Siyao Peng and Barbara Plank and {Van Der Goot}, Rob",

year = "2024",

month = mar,

day = "1",

language = "English",

pages = "216--221",

editor = "Sophie Henning and Manfred Stede",

booktitle = "Proceedings of The 18th Linguistic Annotation Workshop (LAW-XVIII)",

publisher = "Association for Computational Linguistics",

address = "United States",

}

EEVEE: An Easy Annotation Tool for Natural Language Processing. / Sorensen, Axel; Peng, Siyao; Plank, Barbara et al.
Proceedings of The 18th Linguistic Annotation Workshop (LAW-XVIII). ed. / Sophie Henning; Manfred Stede. St. Julians, Malta: Association for Computational Linguistics, 2024. p. 216-221.

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

TY - GEN

T1 - EEVEE: An Easy Annotation Tool for Natural Language Processing

AU - Sorensen, Axel

AU - Peng, Siyao

AU - Plank, Barbara

AU - Van Der Goot, Rob

PY - 2024/3/1

Y1 - 2024/3/1

N2 - Annotation tools are the starting point for creating Natural Language Processing (NLP) datasets. There is a wide variety of tools available; setting up these tools is however a hindrance. We propose Eevee, an annotation tool focused on simplicity, efficiency, and ease of use. It can run directly in the browser (no setup required) and uses tab-separated files (as opposed to character offsets or task-specific formats) for annotation. It allows for annotation of multiple tasks on a single dataset and supports four task-types: sequence labeling, span labeling, text classification and seq2seq.

AB - Annotation tools are the starting point for creating Natural Language Processing (NLP) datasets. There is a wide variety of tools available; setting up these tools is however a hindrance. We propose Eevee, an annotation tool focused on simplicity, efficiency, and ease of use. It can run directly in the browser (no setup required) and uses tab-separated files (as opposed to character offsets or task-specific formats) for annotation. It allows for annotation of multiple tasks on a single dataset and supports four task-types: sequence labeling, span labeling, text classification and seq2seq.

M3 - Article in proceedings

SP - 216

EP - 221

BT - Proceedings of The 18th Linguistic Annotation Workshop (LAW-XVIII)

A2 - Henning, Sophie

A2 - Stede, Manfred

PB - Association for Computational Linguistics

CY - St. Julians, Malta

ER -

EEVEE: An Easy Annotation Tool for Natural Language Processing

Abstract

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