What question did this study set out to answer?

The research aims to evaluate and compare the performance of various systems on text normalization and named entity recognition tasks.

January 1, 2015Open Access

Shared Tasks of the 2015 Workshop on Noisy User-generated Text: Twitter Lexical Normalization and Named Entity Recognition

Key Points

The research aims to evaluate and compare the performance of various systems on text normalization and named entity recognition tasks.
Conducted two shared tasks: text normalization with 10 participants and named entity tagging with 8 participants.
Outlined the annotation process and provided dataset statistics.
Presented a high-level overview of the participating systems for text normalization.
Summarized the performance metrics of the named entity detection systems.

Abstract

This paper presents the results of the two shared tasks associated with W-NUT 2015: (1) a text normalization task with 10 participants; and (2) a named entity tagging task with 8 participants. We outline the task, annotation process and dataset statistics, and provide a high-level overview of the participating systems for each shared task.

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Cite This Study

Baldwin et al. (Thu,) studied this question.

synapsesocial.com/papers/6a11e922a8e383061b8e1d6c https://doi.org/https://doi.org/10.18653/v1/w15-4319

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