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Starspace is a vector embedding framework designed for training high-dimensional representations of text and images. It functions as a machine learning system for neural ranking, text classification, and knowledge graph embedding, mapping different object types into a shared numerical space to facilitate retrieval and prediction tasks. The system includes specialized tools for knowledge graph completion and link prediction by representing entities and their relationships within a multi-relational vector space. It further provides capabilities for semantic content recommendation and large-scal
Frog is an integration of memory-based natural language processing (NLP) modules developed for Dutch. All NLP modules are based on Timbl, the Tilburg memory-based learning software package.
BLLIP reranking parser (also known as Charniak-Johnson parser, Charniak parser, Brown reranking parser) See http://pypi.python.org/pypi/bllipparser/ for Python module.
MITIE: library and tools for information extraction
The main features of mit-nlp/mitie are: Information Extraction, Natural Language Processing, C++ NLP Libraries.
Projects with overlapping indexed features include: languagemachines/ucto — Unicode tokeniser. Ucto tokenizes text files: it separates words from punctuation, and splits sentences. It offers… languagemachines/libfolia — FoLiA library for C++. bllip/bllip-parser — BLLIP reranking parser (also known as Charniak-Johnson parser, Charniak parser, Brown reranking parser) See… facebookresearch/starspace — Starspace is a vector embedding framework designed for training high-dimensional representations of text and images.… languagemachines/frog — Frog is an integration of memory-based natural language processing (NLP) modules developed for Dutch. All NLP modules… meta-toolkit/meta — A Modern C++ Data Sciences Toolkit.