What´s new

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Short list of what's new in @ Note2

Summary of features - Anote2 vs Anote


  • Run Text miming workflows
  • Eliminates dependency on Perl; fully implemented in Java; easier to install and run in different platforms;
  • MySql or H2 embedded database are used to store all relevant information (including annotations); data model extended and re-organized to provide the core of the application;
  • Organization in a set of plug-ins taking advantage of AI Bench plug-in system; improves modularity; makes easier adding new functionality and alternatives for different processes;
  • Code was re-organized using Java interfaces for all relevant concepts and processes, making easier the integration of third party applications; MVC notions from AI Bench are better used to provide organized GUIs; core plug-ins define basic data structures and the interface of basic processes;
  • Indication of progress in time consuming processes.
  • Statistics and reports for all operation and datatypes
  • Settings configuration system
  • Update System

Publication Manager

  • Add Patent document and Patent search
  • Add Springer search
  • PDF Retrieval from multiple sources
  • Query Update
  • Query Management system; larger number of options available
  • Possibility of including external publications manually
  • Publication Labeling and notes

Resources Manager

  • Better lexical resources management(dictionaries, lookup tables, etc)
  • Add Ontologies, rules ageneral lexical words (Stop Words)
  • More loaders and an interface allowing the easy implementation of new loaders


  • Notion of corpus/ corpora added to @Note
  • Allows creating corpus from the publication manager
  • Allows creating corpus from PDF list
  • Information extraction processes are-organized over corpora
  • Corpus loader: Allows creating corpus from other available corpora (Genia Events, AIMED Protein and @NoteV1).
  • Manual curation of Relations


  • Add and adapt Linnaeus Tagger algorithm
  • Add ABNER and Chenistry tagger (From Gate8)
  • External NERs can be added with an easier interface


  • Add RE algorithms
  • Supports RE over corpora annotated by any NER Process
  • Relation Extraction based in Natural Language processing
  • Relation Co-occurrence
  • Kinetic RE


  • Run Biomedical Text Mining workflows