python-stanford-corenlp

Why we included this project

If your text pipeline leans on Stanford CoreNLP but your code lives in Python, this client spares you the usual shell or Java glue. It talks to the CoreNLP server over the bidirectional interface and returns structured results, token lemmas, part-of-speech tags, named entities, and dependency parses, as protobuf-based Python objects. The tokensregex and semgrex matchers are a handy extra for testing linguistic patterns straight from a client call, which is useful when you are building preprocessing or analysis around CoreNLP's mature annotators. One honest caveat: the project is now archived in favor of stanza, so treat it as reference material or a starting point for a maintained fork rather than the base of a new pipeline.