Named Entity Recognition

A subtask of information extraction that seeks to locate and classify named entities in text into pre-defined categories such as the names of persons, organizations, locations, expressions of times, quantities. [Wikipedia]

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Intended audience Industry and Business, Programmers, Project Managers, Publishers, Researchers and Students, Text and Data miners
Level: Introductory: no previous knowledge is required

This tutorial includes three parts that describe how to use the Wheat Phenotypic Information Extractor and the two end-user applications, WheatIS and AlvisIR, that integrates its results for the use case developed by Inra during the OpenMinTeD project.The application extracts information related to wheat on phenotypes, genes, markers, species, and varieties.

Intended audience Researchers and Students, Text and Data miners
Level: Introductory: no previous knowledge is required

This tutorial explains how to use the Bio Term Hub, an aggregator of biomedical terminologies sourced from manually curated databases, to create a terminology suited to the users need. This terminology can be forwarded to OGER, a dictionary-based named entity recogniser. After the tutorial, the user should be able to use both these tools.
 

OpenMinTeD

Intended audience Industry and Business, Programmers, Researchers and Students, Text and Data miners
Level: Introductory: no previous knowledge is required

In this course we will explain how IXA pipes have been integrated as Docker images in the OpenMinTeD (OMTD) platform and how can they be used (http://ixa2.si.ehu.es/ixa-pipes/).

The aim of IXA pipes is to provide a modular set of ready to use Natural Language Processing (NLP) tools. IXA pipes uses the same approach across NLP tasks in order to create robust processors both across domains and languages.
 

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Intended audience Industry and Business, Policy makers and Funders, Project Managers, Publishers, Researchers and Students, Text and Data miners
Level: Introductory: no previous knowledge is required

The objective of this tutorial is to showcase how the Neuroscience use case available at the OpenMinTeD platform can facilitate the curation of neuroscience entities from the literature with the aim of supporting ongoing curation efforts in the Blue Brain Project (BBP), at the École Polytechnique Fédérale de Lausanne (EPFL).
 

Intended audience Industry and Business, Policy makers and Funders, Project Managers, Publishers, Researchers and Students, Text and Data miners
Level: Introductory: no previous knowledge is required

The objective of this tutorial is to showcase the use case of “Extract Metabolites and their Properties and Modes of Actions”. The tutorial describes step-by-step how to create a workflow in the OpenMinTeD platform that can read input from a source and annotate entities useful for the curation of the ChEBI database.
 

Intended audience Industry and Business, Programmers, Project Managers, Publishers, Researchers and Students, Text and Data miners
Level: Introductory: no previous knowledge is required

This tutorial explains how to use the “Arabidopsis Gene Regulation Extractor” application available from the OpenMinTeD platform. It also explains the scientific issues it addresses, and how results of the TDM process can be exploited by researchers through the FlagDB++ application. It is related to the AS-D “Information Extraction of Mechanisms Involved in Plant” Development use case developed in the OpenMinTeD project.
 

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
Level: Introductory: aware of

The OpenMinTeD project offers an integrated registry of text mining components alongside a powerful corpus builder. The platform can be used to identify a set of documents of interest and then run a text mining algorithm on those documents to quickly extract the information hidden away inside of them.

A journalist might want to use the OpenMinTeD platform when they need to learn about a specific scientific area of int...

Intended audience Programmers, Researchers and Students, Text and Data miners
Level: Intermediate: able to

The Unstructured Information Management Architecture (UIMA) is a widely used software framework and specification to create multi modal analysis systems, in particular for Natural Language Processing (NLP) purposes. Especially, the OpenMinted platform builds upon this architecture enhancing the need for NLP tools that comply to UIMA.In this tutorial, we try to explain how to wrap your Java NLP tool into the UIMA CAS and (Commen Analysis Sys...

COURSE: VineSum
Intended audience Text and Data miners
Level: Intermediate: able to

A software component for vine/grape variety named entity extraction and clustering

VineSum is an openMinTeD executable component that, given a collection of documents, it: 

    - Performs NER extraction, identifying four entity types: a) vine varieties b) persons c) locations d...