NLTK in research is probably mostly used as glue, its corpus interface, and its standard wrappers to common libraries. Everyone using it for research will do so

NLTK in research is probably mostly used as glue, its corpus interface, and its standard wrappers to common libraries. Everyone using it for research will do something like "I used data from NLTK, pushed it through my custom parser, and here's how it compares to the wrapped parsers that NLTK also interfaces with". That's why the maintainer said, basically, "nope, we only implement the standard algorithms". Most of the researchers want to get standard data, and compare their new algorithm to the standard algorithms that every other researcher uses.