#entity relationship

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One of the most useful applications of natural language processing (NLP) technology is information extraction from unstructured texts — contracts, financial documents, healthcare records, etc. — that enables automatic data query to derive new insights. Traditionally, named entity recognition has been widely used to identify entities inside a text and store the data for advanced querying and filtering.

Whether it’s receipts, contracts, financial documents, or invoices, etc., automating information retrieval will help you increase your business efficiency and productivity at a fraction of the cost. However, this amazing feat will not be possible without text annotation.

Annotating text to train and fine-tune a model for your own use is crucial. Therefore, choosing the right annotation tool with low UI friction and maximum automation is of the utmost importance.

OCR processes images of text and converts that text into machine-readable forms. UBIAI’s OCR feature allows you to perform NER, relation extraction, and classification annotation directly on native PDF documents, scanned images or pictures from your phone without losing any layout information, resulting in a significant boost of your NLP model performance.

Many companies that provide machine learning text annotations help you successfully run your Artificial Intelligence and Machine Learning projects.

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