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This project provides free (even for commercial use) state-of-the-art information extraction tools. The current release includes tools for performing named entity extraction and binary relation detection as well as tools for training custom extractors and relation detectors. MITIE is built on top of dlib, a high-performance machine-learning library[1], MITIE makes use of several state-of-the-art techniques including the use of distributional word embeddings[2] and Structural Support Vector Machines[3]. MITIE offers several pre-trained models providing varying levels of support for both English, Spanish, and German trained using a variety of linguistic resources (e.g., CoNLL 2003, ACE, Wikipedia, Freebase, and Gigaword). The core MITIE software is written in C++, but bindings for several other software languages including Python, R, Java, C, and MATLAB allow a user to quickly integrate MITIE into his/her own applications.
Features
- MITIE's primary API is a C API which is documented in the mitie.h header file
- MITIE comes with a basic streaming NER tool
- Compile MITIE as a shared library
- Compile MITIE using OpenBLAS
- Use MITIE from a Python 2.7 program
- Precompiled Python 2.7 binaries
- Precompiled Java 64bit binaries
Project Samples
