@Misc{Alexiev2014-LinguisticLD,
  author       = {Vladimir Alexiev},
  title        = {{Linguistic Linked Data}},
  howpublished = {presentation},
  month        = oct,
  year         = 2014,
  url          = {https://rawgit2.com/VladimirAlexiev/multisensor/master/20141008-Linguistic-LD/index-full.html},
  url_Slides   = {https://rawgit2.com/VladimirAlexiev/multisensor/master/20141008-Linguistic-LD/index.html},
  keywords     = {Linguistic Linked Data, NLP, NLP2RDF, NIF, OLIA, NERD, MARL, BabelNet, FrameNet, WordNet},
  booktitle    = {{Multisensor Project Meeting}},
  address      = {Bonn, Germany},
  abstract     = {There's been a huge drive in recent years to represent NLP data as RDF. NLP data is usually large, so does it make sense to represent it as RDF? What's the benefit? Ontologies, schemas and groups include: GRaF ITS2 FISE LAF LD4LT LEMON LIME LMF MARL NERD NIF NLP2RDF OLIA OntoLex OntoLing OntoTag Penn Stanford... my oh my! There are a lot of linguistic resources available that can be used profitably: BabelNet FrameNet GOLD ISOcat LemonUBY Multitext OmegaNet UBY VerbNet Wiktionary WordNet.},
}

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