Using Named-Entity Recognition to Filter Sensitive Information in Free Text for External APIs
By
thunderbong
Crisp on the outside, thoughtful on the inside. A keeper.
Summary
The article discusses methods for filtering sensitive information in free text before sending it to external APIs, particularly for chatbots and LLMs. It explains that while parameter-based filtering works for structured data, free text requires more sophisticated approaches. The piece highlights the limitations of regex-based filtering and introduces named-entity recognition (NER) as a more effective solution for identifying and redacting various types of sensitive information that cannot be captured with simple pattern matching.
Key quotes
· 4 pulledFiltering the entire string may not be an option if an external API needs to process the value
You could use a regex to filter sensitive information, but that won't capture everything
Fortunately, named-entity recognition (NER) can be used to identify sensitive information
Not all sensitive information can be captured with a regex
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