SemiNER - Named Entity Labeler

Grzegorz Chrupala <gchrupala@lsv.uni-saarland.de>

Version 0.3

SemiNER is a tool for Named Entity labeleling. This 
release includes models trained on the German CoNLL data with
features extracted from a large unlabeled German corpus.

The easiest way to start using SemiNER is to run the following command
from the top-level sequor directory:

> cabal install --prefix=`pwd`

This assumes that you have already installed the Haskell platform from
http://www.haskell.org/platform

Contact the author me if you encounter problems.

USAGE:

There are two pretrained models: full (which uses all the features
from training data, including lemmas, POS tags and chunk tags) and raw
(which only uses word features and cluster id features. You don't need
to run any additional preprocessing steps to run the raw model.

To label new data using the raw pre-trained model:
> bin/seminer raw < INPUT-FILE > OUTPUT-FILE
To label new data using the full pre-trained model:
> bin/seminer full < INPUT-FILE > OUTPUT-FILE


The CoNLL input format is one token per line, sentences separated by a
blank line.