Parallel work with two taggers

I am working on the part-of-speech-tagging of the German political speeches corpus, and I would like to get tags from two different kinds of POS-taggers :

  • on one hand the TreeTagger, a hidden Markov model tagger which uses statistical rules and decision trees,
  • on the other the Stanford POS-Tagger, a bidirectional maximum entropy tagger.

This is easier said than done.

I am using the 2011-05-18 version of the Stanford Tagger with its standard models for German (I don’t know if any of the problems I encountered would be different with a newer or still-to-come version) and the basic version of the TreeTagger with the standard model for German.

A few issues

  • The Stanford-Tagger does not recognize the € symbol, and as in similar cases it adds a word and a tag explaining that the symbol is unknown.
  • There are non-breaking hyphens in my corpus, which (in my opinion) result from a too hasty cleaning of the texts before there where published, or a strange publication software. All the hyphens appear as white spaces, including in the HTML source, but in fact they are a Unicode sign. The TreeTagger treats them as spaces, the Stanford Tagger spits an error, marks ...
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Quick review of the Falko Project

The Falko Project is an error-annotated corpus of German as a foreign language, maintained by the Humboldt Universität Berlin who made it publicly accessible.

Recently a new search engine was made available, practically replacing the old CQP interface. This tool is named ANNIS2 and can handle complex queries on the corpus.


There are several subcorpora, and apparently more to come. The texts were written by advanced learners of German. There are most notably summaries (with the original texts and a comparable corpus of summaries written by native-speakers), essays who come from different locations (with the same type of comparable corpus) and a ‘longitudinal’ corpus coming from students of the Georgetown-University of Washington.

The corpora are annotated by a part-of-speech tagger (the TreeTagger) so that word types and lemmas are known but most of all the mistakes can be found, with several hypotheses at different levels (mainly what the correct sentence would be and what might be the reason of the mistake).


The engine (ANNIS2) has a good tutorial (in English by the way) so that it is not that difficult to search for complex patterns across the subcorpora. It seems also efficient in terms of speed. You may ...

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A fast bash pipe for TreeTagger

I have been working with the part-of-speech tagger developed at the IMS Stuttgart TreeTagger since my master thesis. It performs well on german texts as one could easily suppose, since it was one of its primary purposes. One major problem is that it’s poorly documented, so I would like to share the way that I found to pass things to TreeTagger through a pipe.

The first thing is that TreeTagger doesn’t take Unicode strings, as it dates back to the nineties. So you have to convert whatever you pass to ISO-8859-1, which the iconv software with the translit option set does very well. It means here “find an equivalent if the character cannot be exactly translated”.

Then you have to define the options that you want to use. I put the most frequent ones in the example.


The advantage of a pipe is that you can clean the text while passing it to the tagger. Here is one way of doing it, by using the text editor sed to : 1. remove the trailing white lines 2. replace everything that’s more than one space by one space and 3. replacing spaces by new lines.

This way ...

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