Xiaoshi Zhong Erik Cambria Zhong Time Expression and Named Entity Recognition

Time Expression and Named Entity Recognition

von Xiaoshi Zhong Erik Cambria

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Beschreibung

This book presents a synthetic analysis about the characteristics of time expressions and named entities, and some proposed methods for leveraging these characteristics to recognize time expressions and named entities from unstructured text. For modeling these two kinds of entities, the authors propose a rule-based method that introduces an abstracted layer between the specific words and the rules, and two learning-based methods that define a new type of tagging scheme based on the constituents of the entities, different from conventional position-based tagging schemes that cause the problem of inconsistent tag assignment. The authors also find that the length-frequency of entities follows a family of power-law distributions. This finding opens a door, complementary to the rank-frequency of words, to understand our communicative system in terms of language use.


This book presents a synthetic analysis about the characteristics of time expressions and named entities, and some proposed methods for leveraging these characteristics to recognize time expressions and named entities from unstructured text. For modeling these two kinds of entities, the authors propose a rule-based method that introduces an abstracted layer between the specific words and the rules, and two learning-based methods that define a new type of tagging scheme based on the constituents of the entities, different from conventional position-based tagging schemes that cause the problem of inconsistent tag assignment. The authors also find that the length-frequency of entities follows a family of power-law distributions. This finding opens a door, complementary to the rank-frequency of words, to understand our communicative system in terms of language use.


Presents a synthetic analysis about the characteristics of timexes and entities Reports the latest findings on recognizing timexes and entities from unstructured text Opens a door to examine whether multiple joint tasks enhance each other under a joint modeling framework

Autor*in

Xiaoshi Zhong

Themen in »Time Expression and Named Entity Recognition«

Time Expression Named Entity Syntactic Token Types Tagging Schemes Power-Law Distribution

Stimmen zu »Time Expression and Named Entity Recognition«

Details

ISBN: 9783030789602
Verlag: Springer International Publishing
Erscheinung: 24.08.2021

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