Recently, we were tagging a lot of texts with spaCy in order to extract organization names. We faced a problem: many entities tagged by spaCy were not valid organization names at all. And it wasn’t actually the problem of spaCy itself: all extracted entities, at first sight, did look like organization names. The result could be better if we trained spaCy models more. However, this approach required a large corpus of properly labeled data which should also include a proper context. So we needed a simpler solution to filter out the wrong data.
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