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AddDiscourse

Explicit Discourse Connectives Tagger Java Implementation based on the work described in
Emily Pitler and Ani Nenkova. Using Syntax to Disambiguate Explicit Discourse Connectives in Text. Proceedings of the ACL-IJCNLP 2009 Conference Short Papers, pages 13-16.

Explicit Discourse Connectives Tagger - December 14, 2009

This tool is built to automatically identify explicit discourse connectives and their sense (Expansion, Contingency, Comparison, Temporal). It takes syntactic parse trees as input and outputs augmented trees with tags for each discourse connective.

This tool is based on the work described in: Emily Pitler and Ani Nenkova. Using Syntax to Disambiguate Explicit Discourse Connectives in Text. Proceedings of the ACL-IJCNLP 2009 Conference Short Papers, pages 13-16.

This will read in the parse trees in sample-parse.txt and output them augmented with discourse connective tags. Each word or phrase which can be a discourse connective is tagged with an ID number and its predicted sense (or 0 if predicted non-discourse). The word, its id, and its sense are separated by # marks.

The possible senses are: Expansion, Contingency, Comparison, Temporal, or 0 (non-discourse usage). The four discourse usage tags correspond to the top level of the sense hierarchy in the Penn Discourse Treebank.

For example, as#6#Temporal should be read as 'the word as in this context has an id of 6, and a sense of Temporal'.

Id numbers are used to identify multi-word or long-distance connectives. The shared id numbers for: In#0#Expansion and addition#0#Expansion show that ``In addition'' is just one instance of an Expansion connective.

The resources folder contains two files: connectives.info and connectives.txt.

connectives.info contain the learned feature weights. This is the output of Mallet's MaxEnt classifier trained on sections 2-22 of version 2 of the Penn Discourse Treebank.

connectives.txt contains a list of the words and phrases to consider as possible connectives.
If you wish, you may add to this list. Words or phrases that were unknown at training time will be classified solely on the basis of their syntactic context.
Long-distance connectives (like ``On the one hand...on the other hand") are specified using .. between the first half and the second half (on the one hand..on the other hand).