I've been playing around with sentence embeddings to search documents, but I wonder how useful they are as a natural language interface for a database. The way one might phrase a question might be very different content wise from how the document describes the answer. Maybe it might be possible to do some type of transform where the question is transformed into a possible answer and then turned into a embedding but I…
You have late-interaction models, which replace the dot product with a few transformer layers and are able to learn complex semantics.
Of course this would adversely affect latency and embedding size, so you might want to compress and cache the answers, hence (shameless plug):