Relation Extraction

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

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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 concerns scientific publications in non-English languages. The component has been shared as a Docker a...

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.
 

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.

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 “Microbial biodiversity” use case developed in the OpenMinTeD project.
 

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 ontology as the reference ontology. This tutorial shows how to install BOLSTM, classify any text using thi...

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 other tasks to make it easier to keep text mining results up-to-date.

OpenMinTeD platform a...

By  Estelle Chaix , Louise Deléger, Robert Bossy, Claire Nédellec