Hase provides Haskell bindings for the Senna NLP toolkit, supporting
- Part of Speech tagging (POS)
- Chunking (CHK)
- Name Entity Recognition (NER)
- Semantic Role Labeling (SRL)
At first, please download Senna and
extract the Senna source files into
tar command below
does just that.
tar -xzf senna-v3.0.tgz -C foreign/
cabal configure cabal build
to build hase. You can run the example program by executing
cabal run example
Finally, if you want to install this package, run
Here's a simple example to tokenize and process a sentence read from stdin.
module Main where import NLP.Senna main = withContext $ \ctx -> do tokenize ctx =<< getLine print =<< (process ctx :: IO [Token]) print =<< (process ctx :: IO [Maybe POS]) print =<< (process ctx :: IO [(CHK, Phrase)]) print =<< (process ctx :: IO [(NER, Phrase)]) print =<< (process ctx :: IO [[(SRL, Phrase)]])
The Context type holds the internal C library state. You can either manage Context manually by calling createContext and freeContext, or you can use withContext, which automatically creates and frees the Context for you.
Once the Context is created, you pass a sentence to the tokenize function. The tokenize function sets up Context to work with your sentence. Then you can call process to perform various NLP tasks on the previously tokenized sentence.
The Context is memory hungry (200 MB) and should only be setup once. Processing multiple sentences works by alternately calling tokenize and process on the same Context.
hase is released under MIT license. You can find a copy of the MIT License in the LICENSE file.