spaCy Ecosystem
spaCy is a free library for advanced Natural Language Processing (NLP) in Python. It’s designed specifically for production use and helps you build applications that process and “understand” large volumes of text. It can be used to build information extraction or natural language understanding systems.
Keywords
Languages
Lexicon-NLP-Lab
indonesian-ner-spacy
Fine-tuning SpaCy for Indonesian Named Entity Recognition (NER) with custom dataset
spacy-ner-hf-space
A webapp built using Gradio for demonstrating the capabilities of the Spacy NER pipeline
NER-Model-for-Company-Names-GOST-and-Product-Names-Detect
Модель NER для определения названий компаний, стандартов госта и названий товаров с точностью 97%
dose_instruction_parser
Parsing prescription dose instructions using Named Entity Recognition and rules
spacy-partial-tagger
A simple library for training named entity recognition model from partially annotated data
healthsea
Healthsea is a spaCy pipeline for analyzing user reviews of supplementary products for their effects on health
Wikia-and-Wikipedia-EL-Dataset-Creator
You can create datasets from Wikia/Wikipedia that can be used for entity recognition and Entity Linking
ner-annotator
GUI useful to manually annotate text for Named Entity Recognition purposes
presidio-research
This package features data-science related tasks for developing new recognizers for Presidio
topicrankpy
A Python package to get useful information from documents using TopicRank Algorithm
spoken2written
A source of python package which converts language styles in speech to its equivalent written form
nlp-cheat-sheet-python
NLP Cheat Sheet, Python, spacy, LexNPL, NLTK, tokenization, stemming, sentence detection, named entity recognition
