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  • 1
    Diffgram

    Diffgram

    Training data (data labeling, annotation, workflow) for all data types

    ...This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This includes the activities of annotation, which produces structured data; ready to be consumed by a machine learning model. Annotation is required because raw media is considered to be unstructured and not usable without it. That’s why training data is required for many modern machine learning use cases including computer vision, natural language processing and speech recognition.
    Downloads: 8 This Week
    Last Update:
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  • 2

    MITRE Annotation Toolkit

    A toolkit for managing and manipulating text annotations

    The MITRE Annotation Toolkit (MAT) is a suite of tools which can be used for automated and human tagging of annotations. Annotation is a process, used mostly by researchers in natural language processing, of enhancing documents with information about the various phrase types the documents contain. MAT supports both UI interaction and command-line interaction, and provides various levels of control over the overall annotation process.
    Downloads: 4 This Week
    Last Update:
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  • 3

    BioC

    We describe a simple XML format to share text documents and annotation

    A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are...
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    Downloads: 11 This Week
    Last Update:
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