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MicroNeel: Combining NLP Tools to Perform Named Entity Detection and Linking on Microposts

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Conference object , Book , Article 01 Jan 2016 Italy English Publisher:Accademia University PressFunded by:EC | SIMPATICO
Authors: Corcoglioniti, Francesco; Palmero Aprosio, Alessio; Nechaev, Yaroslav; Giuliano, Claudio;

doi: 10.4000/books.aaccademia.1948 , 10.5281/zenodo.1048867 , 10.5281/zenodo.1048868

handle: 11572/193674 , 11572/413064 , 20.500.13089/1d4k

MicroNeel: Combining NLP Tools to Perform Named Entity Detection and Linking on Microposts

Abstract

In this paper we present the MicroNeel system for Named Entity Recognition and Entity Linking on Italian microposts, which participated in the NEEL-IT task at EVALITA 2016. MicroNeel combines The Wiki Machine and Tint, two standard NLP tools, with comprehensive tweet preprocessing, the Twitter-DBpedia alignments from the Social Media Toolkit resource, and rule-based or supervised merging of produced annotations.

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Italy
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Keywords

Computer Science (all), Twitter, The Wiki Machine, Entity Linking, Named Entity Recognition, Tint, Social Media Toolkit, MicroNeel, Microposts

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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OpenAIRE UsageCountsViews provided by UsageCounts
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6
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12
6
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