publication . Report . Other literature type . 2018

BigDataGrapes D3.4 - Linguistic Pipelines for Semantic Enrichment

Yankova; Milena; Alexiev, Vladimir; Primov, Todor; Rusinov, Nikola;
Open Access English
  • Published: 20 Dec 2018
Abstract
This deliverable is the first report on the progress of T3.4 Semantic Enrichment. It will describe the progress on the design of advanced text analytics pipelines aiming to extract and semantically annotate information from unstructured textual data sources from the Big Data Grapes (BDG) data pool. It will describe in detail a proposed approach for named entity recognition and relation extraction from large natural language resources like scientific research, news articles and webpages- this approach has both proven very successful in practice with a variety of large corpora and is flexible enough to adjust to the specific content types relevant to the BDG use c...
Subjects
free text keywords: Semantic; linguistic pipelines; text analytics
Funded by
EC| BigDataGrapes
Project
BigDataGrapes
Big Data to Enable Global Disruption of the Grapevine-powered Industries
  • Funder: European Commission (EC)
  • Project Code: 780751
  • Funding stream: H2020 | RIA
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ZENODO
Report . 2018
Provider: ZENODO
Zenodo
Other literature type . 2018
Provider: Datacite
Zenodo
Other literature type . 2018
Provider: Datacite
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