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  • Lexicon

    Named Entity Recognition (NER)

    The automatic detection and labeling of proper names (entities) in texts. Example: Angela Merkel and Frau Merkel refer to the same person in two sentences.

    Natural Language Generation (NLG)

    Natural Language Generation. The generation of text (natural language) using machine learning.

    Natural Language Processing (NLP)

    Natural language processing is the automatic processing of natural language. It uses methods from computational linguistics, artificial intelligence and statistics to recognise, understand, interpret and generate language. These insights can then be used to translate or rewrite texts, for example.

    Natural Language Understanding (NLU)

    Natural Language Understanding describes the ability of machines to understand natural language. This includes both reading and writing natural language and analyzing meaning and context.

    neural networks

    Neural networks are artificial intelligence models modeled on the human brain. They consist of a series of processing units that are interconnected.

    An artificial neural network consists of layers of interconnected units (neurons) that pass information to each other under certain conditions. Each unit processes a specific signal and passes it on to the next unit. The network learns by processing signals and adjusting the connections between units.

    In Deep Learning, there are usually many such layers, each with a very large number of neurons, which makes training very computationally intensive.

    normalization of texts

    Normalization of texts describes the standardization of text structure and punctuation. For example, all quotation marks and dashes are normalized to one character each, as are section markers such as lines or markers for chapter headings.