Indexing Documents for Large Scale Question Answering Systems
Blog post from deepset
To properly index documents for large-scale question answering systems with Haystack, it's essential to learn how to clean, split, and index text data. Haystack provides tools like PreProcessor, Crawler, Converter, and DocumentStore to make working with text data easier. The document indexing process can be achieved through different methods: defining an indexing pipeline via YAML configuration, using the REST API for continuous indexing of documents, or directly adding documents to the database. Each method has its own advantages and is suited for specific use cases. By choosing the right approach, developers can successfully deploy a Haystack question answering system with their own dataset.
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