What's Wrong With My NLP? 0.2.3

A visualizer for Natural Language Processing problems.
What's Wrong With My NLP? is a visualizer for Natural Language Processing problems.

Main features:

  • (Jointly) visualize:
  • syntactic dependency graphs
  • semantic dependency graphs (a la CoNLL 2008)
  • Chunks (such as syntactic chunks, NER chunks, SRL chunks etc.)
  • Compare gold standard trees to your generated trees (e.g. highlight false positive and negative dependency edges)
  • Filter trees and visualize only what's necessary, for example:
  • only dependency edges with certain labels
  • only the edges between certain tokens
  • Search corpora for sentences with certain attributes using powerful search expressions, for example:
  • search for all sentences that contain the word "vantage" and the pos tag sequence DT NN
  • search for all sentences that contain false positive edges and the word "vantage"
  • Reads:
  • CoNLL 2000, 2002, 2003, 2004, 2006 and 2008 format
  • Lisp S-Expressions
  • Malt-Tab format
  • markov thebeast format
  • Export to EPS

last updated on:
July 6th, 2010, 10:38 GMT
price:
FREE!
developed by:
Sebastian Riedel
homepage:
code.google.com
license type:
GPL (GNU General Public License) 
category:
ROOT \ Science and Engineering \ Artificial Intelligence

FREE!

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2 Screenshots
What's Wrong With My NLP? - This is a fraction of a semantic dependency graph that compares a gold labelling to a system labelling. The red edges are false positives, the blue ones false negatives and the black ones are matches:What's Wrong With My NLP? - This shows the comparison of two shallow parses and two NER labellings (again false positives are red, false negatives are blue and matches are black):
What's New in This Release:
  • This release allows you to provide additional information about edges and spans in your predictions. For example, for first order dependency parsing models, you can show feature vectors associated with false positive or negative edges. This can be a very helpful feature when debugging probabilistic models of language. The release also contains minor bugfixes for loading data.
read full changelog

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