Custom or out of the box? Choose the right NLP model for your enterprise Sponsored by IBM
“What we’re doing is mimicking the behavior of lawyers in everyday work,” James Lee, co-founder and CEO of LegalMation, said during theSome tasks that would normally take a lawyer eight hours can now be completed in two minutes thanks to NLP.
Whether you choose an out-of-the-box approach or a custom model will depend on your business objectives, your industry and even where you live or do business. Here are some key factors to consider. For many companies, building NLP solutions for text-based analysis is time-consuming and cumbersome. Often, they must spend hundreds of hours sorting through documents and labeling keywords and sentiments in the text.
One thing to remember: Prebuilt NLP models are often trained on general-purpose data sources. As a result, they tend not to be tailored to any single industry or domain, which often requires the understanding of specialized terms and intentions. When NLP models need to understand industry-specific lingo, a pretrained model may serve only limited needs. Across different industries, some entities will have different meanings, so an out-of-the-box model may not be able to pick up on these nuances.
Custom NLP models can be trained to understand these differences—as well as other nuances, meanings and relationships specific to industries, locales and the tasks you assign it.
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