课程: Hands-On Natural Language Processing

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Data preprocessing for custom NER

Data preprocessing for custom NER

课程: Hands-On Natural Language Processing

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Data preprocessing for custom NER

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- The general idea behind data annotation for named entity recognition is that the entities of interest get tagged with the desired labels in an appropriate format, depending on the training data. In this notebook, we will learn how to notate data in a format that is compatible with Spacy a natural longer processing library that uses an open source notebook compatible library called Spacy annotator. The sample text used in this video is a snippet from LinkedIn's Wikipedia page. First we install the library using pip. Then we input the necessary models. Then we save the text into a variable called sample text. We then split the sample text using the next line corrector and save into a list called sample text list. After removing the empty strings there are 15 sentences in total. Now go ahead to save the sample text list into the pd data frame called DF with a column name: text. To process our raw text. We load a phython…

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