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MITIE: library and tools for information extraction
| Date | Stars |
|---|---|
| 2026-07-24 | 2959 |
| 2026-07-25 | 2959 |
| 2026-07-28 | 2959 |
| 2026-07-30 | 2959 |
| 2026-08-09 | 2961 |
| 2026-08-17 | 2962 |
| 2026-08-21 | 2963 |
| 2026-08-22 | 2962 |
| 2026-09-08 | 2960 |
| 2026-09-20 | 2960 |
Today
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MITIE: MIT Information Extraction ===== This project provides free (even for commercial use) [state-of-the-art](../../wiki/Evaluation) information extraction tools. The current release includes tools for performing [named entity extraction](http://blog.dlib.net/2014/04/mitie-completely-free-and-state-of-art.html) and [binary relation detection](http://blog.dlib.net/2014/07/mitie-v02-released-now-includes-python.html) as well as tools for training custom extractors and relation detectors. MITIE is built on top of [dlib](http://dlib.net), 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](https://github.com/mit-nlp/MITIE/releases/download/v0.4/freebase_wikipedia_binary_relation_training_data_v1.0.tar.bz2), 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. Outside projects have created API bindings for [OCaml](https://github.com/travisbrady/omitie), [.NET](https://github.com/BayardRock/MITIE-Dot-Net), [.NET Core](https://github.com/slamj1/MitieNetCore), [PHP](https://github.com/ankane/mitie-php), and [Ruby](https://github.com/ankane/mitie). There is also an [interactive tool](https://github.com/Sotera/mitie-trainer) for labeling data and training MITIE. # Using MITIE MITIE's primary API is a C API which is documented in the [mitie.h](mitielib/include/mitie.h) header file. Beyond this, there are many [example programs](examples/) showing how to use MITIE from C, C++, Java, R, or Python 2.7. ### Initial Setup Before you can run the provided examples you will need to download the trained model files which you can do by running: ``` make MITIE-models ``` or by simply downloading the [MITIE-models-v0.2.tar.bz2](https://github.com/mit-nlp/MITIE/releases/download/v0.4/MITIE-models-v0.2.tar.bz2) file and extracting it in your MITIE folder. Note that the Spanish and German models are supplied in separate downloads. So if you want to use the Spanish NER model then download [MITIE-models-v0.2-Spanish.zip](https://github.com/mit-nlp/MITIE/releases/download/v0.4/MITIE-models-v0.2-Spanish.zip) and extract it into your MITIE folder. Similarly for the German model: [MITIE-models-v0.2-German.tar.bz2](https://github.com/mit-nlp/MITIE/releases/download/v0.4/MITIE-models-v0.2-German.tar.bz2) ### Using MITIE from the command line MITIE comes with a basic streaming NER tool. So you can tell MITIE to process each line of a text file independently and output marked up text with the command: ``` cat sample_text.txt | ./ner_stream MITIE-models/english/ner_model.dat ``` The ner_stream executable can be compiled by running `make` in the top level MITIE folder or by navigating to the [tools/ner_stream](tools/ner_stream) folder and running `make` or using CMake to build it which can be done with the following commands: ``` cd tools/ner_stream mkdir build cd build cmake .. cmake --build . --config Release ``` ### Compiling MITIE as a shared library On a UNIX like system, this can be accomplished by running `make` in the top level MITIE folder or by running: ``` cd mitielib make ``` This produces shared and static library files in the mitielib folder. Or you can use CMake to compile a shared library by typing: ``` cd mitielib mkdir build cd build cmake .. cmake --build . --config Release --target install ``` Either of these methods will create a MITIE shared library in the mitielib folder. ### Compiling MITIE using OpenBLAS If you compile MITIE using cmake then it will automatically find and use any optimized
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:441409461489c62b, topic:natural-language-processing, topic:information-extraction, desc:information extraction