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Time Expression and Named Entity Recognition

Part of the Socio-Affective Computing Book Series (volume 10)

DOI: 10.1007/978-3-030-78961-9

ISBN: 978-3-030-78960-2

Publisher: Springer International Publishing - Springer Journals

Jun 7, 2021

Available

Introduction

Zhong, Xiaoshi; Cambria, Erik

Pages: 1 –13

[This book presents our analysis of intrinsic characteristics of time expressions and named entities, and our use of these characteristics to design algorithms to recognize time expressions and named entities from unstructured text. Regarding time expressions, we find their five common...
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Literature Review

Zhong, Xiaoshi; Cambria, Erik

Pages: 15 –34

[Time expressions and named entities play important roles in data mining, natural language processing, and cognitive computation. Researchers from these areas have devoted considerable effort in the last two decades to define the problem of time expression analysis, design the standards for time...
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Data Analysis

Zhong, Xiaoshi; Cambria, Erik

Pages: 35 –46

[We analyze four diverse datasets about time expressions for their intrinsic characteristics and find five such common characteristics; similarly we analyze two well-known benchmark datasets about named entities for their intrinsic characteristics and find three such common characteristics. For...
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SynTime: Token Types and Heuristic Rules

Zhong, Xiaoshi; Cambria, Erik

Pages: 47 –58

[According to the five common characteristics of time expressions, we propose a type-based approach named SynTime for time expression recognition. Specifically, we define three main syntactic token types, namely time token, modifier, and numeral, to group time-related token regular expressions....
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TOMN: Constituent-Based Tagging Scheme

Zhong, Xiaoshi; Cambria, Erik

Pages: 59 –75

[The characteristics of time expressions drive us to design a learning-based method named TOMN to model time expressions. TOMN defines a constituent-based tagging scheme named TOMN scheme with four tags, namely T, O, M, and N, indicating the constituents of time expression, namely Time token,...
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UGTO: Uncommon Words and Proper Nouns

Zhong, Xiaoshi; Cambria, Erik

Pages: 77 –94

[The conventional position-based tagging schemes that previous research used to model named entities suffer from the problem of inconsistent tag assignment. To overcome the problem of inconsistent tag assignment, we define a constituent-based tagging scheme termed UGTO scheme to model named...
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Conclusion and Future Work

Zhong, Xiaoshi; Cambria, Erik

Pages: 95 –96

[In this book, we present our works on the analysis and recognition of time expressions and named entities. We summarize five intrinsic characteristics about time expressions and three ones about named entities. According to these characteristics, we propose three methods to recognize time...

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