= DELTA-H Online entropy-based model of lexical category acquisition. Grzegorz Chrupala and Afra Alishahi = INSTALL Install the Haskell Platform: http://hackage.haskell.org/platform/ On linux, the following command will install the delta-h executable in the bin directory: cabal install --prefix=`pwd` = USAGE The data directory has an example input file data/goat.txt The other files are CHILDES. To induce a model (i.e. a set of clusters), execute the following: > ./bin/delta-h learn '[-12,0,12]' data/goat.txt The argument '[-12,0,12]' specifies the features to be used (in this case preceding bigram, focus word, and following bigram. Feature ids can be inspected in the source file src/Entropy/Features.hs The model will be stored in data/goat.txt.[-12,0,12].learn.model You can display the model in a human-readable format with: > ./bin/delta-h display data/goat.txt.[-12,0,12].learn.model The learned model can also be used to label input data, without further learning: > ./bin/delta-h label True True data/goat.txt.[-12,0,12].learn.model < \ data/goat.txt The first argument specifies whether to use focus word for labeling, the second argument whether to avoid outputting new cluster ids (not in the model). There is also a command which test the learned model on the word prediction task: > ./bin/delta-h eval-mrr True True data/goat.txt.[-12,0,12].learn.model < \ data/goat.txt The first argument specifies whether to marginalize over all cluster assignments, the second whether to output detailed information. = SOURCES There are some other (currently undocumented) commands: inspect src/Main.hs The main part of the model is implemented in src/Entropy/Algorithm.hs.