scholarly journals A Vector Semantics Approach to the Geoparsing Disambiguation Task for Texts in Spanish

10.29007/pl5h ◽  
2019 ◽  
Author(s):  
Filomeno Alcántara ◽  
Alejandro Molina ◽  
Victor Muñiz
Keyword(s):  
Information Sources ◽  
Semantic Representation ◽  
Online News ◽  
Data Driven ◽  
Entity Extraction ◽  
Named Entity ◽  
News Sources ◽  
Knowledge Based ◽  
Named Entity Extraction ◽  
Future Work

Nowadays, online news sources generate continuous streams of information that includes references to real locations. Linking these locations to coordinates in a map usually requires two steps involving the named entity: extraction and disambiguation. In past years, efforts have been devoted mainly to the first task. Approaches to location disambiguation include knowledge-based, map-based and data-driven methods. In this paper, we present a work in progress for location disambiguation in news documents that uses a vector-semantic representation learned from information sources that include events and geographic descriptions, in order to obtain a ranking for the possible locations. We will describe the proposed method and the results obtained so far, as well as ideas for future work.

scholarly journals Named Entity Extraction for Knowledge Graphs: A Literature Overview

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 32862-32881 ◽  
Author(s):  
Tareq Al-Moslmi ◽  
Marc Gallofre Ocana ◽  
Andreas L. Opdahl ◽  
Csaba Veres
Keyword(s):  
Entity Extraction ◽  
Named Entity ◽  
Named Entity Extraction ◽  
Literature Overview ◽  
Knowledge Graphs

scholarly journals Unsupervised named-entity extraction from the Web: An experimental study

2005 ◽  
Vol 165 (1) ◽  
pp. 91-134 ◽  
Author(s):  
Oren Etzioni ◽  
Michael Cafarella ◽  
Doug Downey ◽  
Ana-Maria Popescu ◽  
Tal Shaked ◽  
...  
Keyword(s):  
Experimental Study ◽  
Entity Extraction ◽  
Named Entity ◽  
Named Entity Extraction ◽  
The Web

The Study on Enlarging Specific Extractor for Technology-Related Named Entity Extraction from Text Collections of Applied Mechanics Field

2011 ◽  
Vol 145 ◽  
pp. 451-454
Author(s):  
Han Gi Kim ◽  
Kuk Jin Bae ◽  
Eun Sun Kim ◽  
Hyuk Hahn
Keyword(s):  
Planning Process ◽  
General Term ◽  
Entity Extraction ◽  
Machinery Industry ◽  
Named Entity ◽  
Named Entity Extraction ◽  
Term Extraction ◽  
Information Research ◽  
New Business ◽  
Machine Industry

This paper presents additional linguistic factors that should be considered to more effectively extract terms from the machinery industry documents by augmenting the general extraction patterns. We expand on the general term extraction patterns with patterns that are tailored for machinery industry documents to improve precision and recall. We establish a theoretical basis for developing a system to support information research in the machinery industry. Using this system, we expect to increase the efficiency of new business planning process in the machine industry.

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