v4.0.0: Simpler installation and integration with SpaCy 2.1+, simple domain-knowledge integration

• Now on pip: pip install neuralcoref.
• Simpler installation which should hopefully be easier to maintain compatible with SpaCy from now on.
• Only use one model and only store/download/cache the coreference resolution model and not the SpaCy models anymore: 10x smaller to download and store
• Compatible w. SpaCy 2.1+: we probably won't seek backward compatibility for older versions of SpaCy since the dependency structure has been cleaned up a lot in SpaCy 2.1 (impressive job by Inès and Matthew! Read about it here)
• New feature to incorporate domain knowledge: conversion dictionary (see details in the readme).

v3.0: Code moved in Cython, removed speakers handling, integration in spaCy pipeline

• Code moved to Cython and Thinc, 50-100x faster. Currently around 2kWPS.
• Removed speakers handling (prevented tighter integration with spaCy)
• Re-factored and simplified code
• Updated documentation

Neuralcoref 2.0 with training code

• You can now train Neuralcoref on your own dataset ,  e.g. other languages! 🎉🎉
• Released our training code + updated code for compatibility with training code
• Updates and bug fixes
• Improved documentation

Updated for stable spaCy v2

• Updated for stable spaCy v2
• improved documentation
• Allow pip installing from git repo

First release

0.1

simple readme