Relation Extraction

The process whereby relations between concepts are derived from text and data.

Navigation

Parent Topic

Click to download taxonomies

Resources by relevance

Course logo
FreeLing Component Tutorial
Intended audience Programmers, Researchers and Students, Text and Data miners
Level: Advanced: apply

The Freeling component provides basic language analysis functionalities (tokenization, lemmatization, Pos Tagging and dependency parsers.) for the variety of languages that Freeling includes (English, Spanish, Portuguese, Italian, French, German, Russian, Catalan, Galician, Croatian, Slovene). The specific usage scenario for this component co...

Course logo
OpenMinTeD Use Case – Funding Mining Extractor
Intended audience Policy makers and Funders, Project Managers, Publishers, Researchers and Students, Text and Data miners
Level: Introductory: aware of

This tutorial walks users through the simple process of creating a workflow in the OpenMinTeD platform that allows them to identify acknowledged projects (i.e. funding information) from scientific publications.
 

Course logo
DataCite Linking
Intended audience Policy makers and Funders, Policy makers and Funders, Project Managers, Publishers, Researchers and Students, Text and Data miners
Level: Introductory: aware of

This tutorial walks users through the simple process of creating a workflow in the OpenMinTeD platform that allows them to extract links to DataCite (https://www.datacite.org) - mainly citations to datasets - from scientific publications.

Course logo
Florilege, a new database of habitats and phenotypes of food microbe flora
Intended audience Programmers, Industry and Business, Project Managers, Researchers and Students, Text and Data miners
Level: Introductory: no previous knowledge is required

This tutorial explains how to use the “Habitat-Phenotype Relation Extractor for Microbes” application available from the OpenMinTeD platform. It also explains the scientific issues it addresses, and how the results of the TDM process can be queried and exploited by researchers through the Florilège application. It is related to the AS-C “Micr...

Course logo
BOLSTM classifying relations via long short term memory networks along biomedical ontologies
Intended audience Programmers, Researchers and Students, Text and Data miners
Level: Intermediate: able to

BO-LSTM is a model based on biomedical ontologies and Long short-term memory networks. The model was developed in python, using keras. To demonstrate its utility, we trained a classification model on the DDI corpus, using the ChEBI ontolo...

Course logo
Ab3P and OpenSesamIE for abbreviations and relations with PubRunner
Intended audience Researchers and Students, Text and Data miners
Level: Introductory: no previous knowledge is required

Abbreviations and basic subject-object relations can be valuable data to understand the context and meaning of text passages. This tutorial explains how to use the two tools Ab3P and OpenSesamIE to extract this data in aggregate. Both tools are integrated into OpenMinTeD using the PubRunner framework which manages format conversion and many o...

Information extraction and other NLP task
By  Martin Krallinger
Publication year: n.d.  |  Text And Data Mining  |  Knowledge Acquisition  |  Knowledge Discovery  |  Knowledge Representation  |  Relation Extraction
Text-mining methods used for information extraction in plant scientific papers Part 5
By  Estelle Chaix
Publication year: 2017  |  Text And Data Mining  |  Information Extraction  |  Relation Extraction
Text mining tools for extracting information about microbial biodiversity in food
By  Estelle Chaix , Louise Deléger, Robert Bossy, Claire Nédellec
Publication year: 2017  |  Information Extraction  |  Relation Extraction  |  Semantic Search
Subscribe to Relation Extraction

Creative Commons badge Unless otherwise stated, all materials created by the FOSTER consortium are licensed under a CREATIVE COMMONS ATTRIBUTION 4.0 INTERNATIONAL LICENSE.



EU flag This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 612425.
This project has also received funding from the European Union's Horizon2020 programme for research, technological development and demonstration under agreement no 741839.