Paper Info
Title
Improving efficiency and accuracy in multilingual entity extraction
Abstract
There has recently been an increased interest in named entity recognition and disambiguation systems at major conferences such as WWW, SIGIR, ACL, KDD, etc. However, most work has focused on algorithms and evaluations, leaving little space for implementation details. In this paper, we discuss some implementation and data processing challenges we encountered while developing a new multilingual version of DBpedia Spotlight that is faster, more accurate and easier to configure. We compare our solution to the previous system, considering time performance, space requirements and accuracy in the context of the Dutch and English languages. Additionally, we report results for 9 additional languages among the largest Wikipedias. Finally, we present challenges and experiences to foment the discussion with other developers interested in recognition and disambiguation of entities in natural language text.
Year
DOI
Venue
2013
10.1145/2506182.2506198
I-SEMANTICS
Keywords
Field
DocType
disambiguation system,improving efficiency,implementation detail,english language,largest wikipedias,additional language,multilingual entity extraction,increased interest,major conference,entity recognition,space requirement,dbpedia spotlight,entity linking,information extraction
Entity linking,Data mining,Data processing,Space requirements,Information retrieval,Computer science,Information extraction,Natural language,Natural language processing,Artificial intelligence,Named-entity recognition
Conference
Citations 
PageRank 
References 
149
4.73
5
Authors
4
Search Limit
100149
Name
Order
Citations
PageRank
Joachim Daiber11577.44
Max Jakob279730.27
Chris Hokamp325614.24
Pablo N. Mendes4107051.09