Sequence Tagging

Many data sets, such as text collections and genetic databases, consist of sequences of distinct values. MALLET includes implementations of widely used sequence algorithms including hidden Markov models (HMMs) and linear chain conditional random fields (CRFs). These algorithms support applications such as gene finding and named-entity recognition.

For a general introduction to CRFs, there are tutorials such as Sutton and McCallum (2006). A developer's guide is available for sequence tagging in MALLET. The MALLET Javadoc API contains information for programmers interested in incorporating sequence tagging into their own work, in the cc.mallet.fst package.

SimpleTagger

SimpleTagger is a command line interface to the MALLET Conditional Random Field (CRF) class. Here we present an extremely simple example showing the use of SimpleTagger to label a sequence of text. Your input file should be in the following format:

    Bill CAPITALIZED noun
    slept non-noun
    here LOWERCASE STOPWORD non-noun

That is, each line represents one token, and has the format:

feature1 feature2 ... featuren label

Then you can train a CRF using SimpleTagger like this (on one line):

java -cp 
 "/home/hough/mallet/class:/home/hough/mallet/lib/mallet-deps.jar"
 cc.mallet.fst.SimpleTagger
  --train true --model-file nouncrf  sample

This assumes that mallet has been installed and built in /home/hough/mallet. Note that we specify the MALLET build directory (/home/hough/mallet/class) and the necessary MALLET jar files (/home/hough/mallet/mallet-deps.jar) in the classpath. The --train true option specifies that we are training, and --model-file nouncrf specifies where we would like the CRF written to. This produces a trained CRF in the file "nouncrf". If we have a file "stest" we would like labelled:

CAPITAL Al
        slept
        here

we can do this with the CRF in file nouncrf by typing:

java -cp
"/home/hough/mallet/class:/home/hough/mallet/lib/mallet-deps.jar"
 cc.mallet.fst.SimpleTagger
--model-file nouncrf  stest

which produces the following output:

Number of predicates: 5
noun CAPITAL Al
non-noun  slept
non-noun  here

To use multi-threaded CRF training, specify the number of threads with --threads:

java -cp
"/home/hough/mallet/class:/home/hough/mallet/lib/mallet-deps.jar"
cc.mallet.fst.SimpleTagger
--train true --model-file nouncrf --threads 8 sample

A list of all the options available with SimpleTagger can be obtained by specifying the --help option:

java -cp
"/home/hough/mallet/class:/home/hough/mallet/lib/mallet-deps.jar"
 cc.mallet.fst.SimpleTagger
--help