Tree visualization of a dependency parser (dependency2tree)

Convert CoNLL output of a dependency parser into a latex or graphviz trees:

download code view github repo


For example, here is a sample output form the the StanfordNLP from which the previous images have been made (using Latex and GraphViz modes, respectively):

1   Paul    Paul    PROPN   NNP Number=Sing 3   nsubj   _   _
2   is  be  AUX VBZ Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin   3   aux _   _
3   drinking    drink   VERB    VBG Tense=Pres|VerbForm=Part    0   root    _   _
4   the the DET DT  Definite=Def|PronType=Art   5   det _   _
5   beer    beer    NOUN    NN  Number=Sing 3   obj _   _
6   he  he  PRON    PRP Case=Nom|Gender=Masc|Number=Sing|Person=3|PronType=Prs  7   nsubj   _   _
7   bought  buy VERB    VBD Mood=Ind|Tense=Past|VerbForm=Fin    5   acl:relcl   _   _
8   this    this    DET DT  Number=Sing|PronType=Dem    9   det _   _
9   morning morning NOUN    NN  Number=Sing 7   obl:tmod    _   _
10  .   .   PUNCT   .   _   3   punct   _   _

And here are the trees using the Latex mode and the GraphViz mode:

Examples of big trees in French (using outputs from Talismane):

Dependency parsers that uses the CoNLL parser includes:

Quick start

There are two modes: Latex or Graphviz. With the Latex mode, all the sentences will be in a file, each on its own page. The script produces a .tex file, named according to the -o option, which is compiled if the -c switch is set (otherwise, just run pdflatex|lualatex <file>.tex). To activate this mode, you must use the the -l swith or the -m latex option:

For example:

python3 -l -o <output.tex> -c <input.conll>


python3 -l -o <output.tex> <input.conll>
pdflatex output.tex # or lualatex

This will produces a output.pdf file containing your trees. Of course, you will need to install pdflatex or lualatex (with your package manager of with texlive).

In the GraphViz mode (the default mode), each sentence is in its own file. If you don't want to compile, you can get graphviz files with:

python3 -o <output.gv> <input.conll>

You will get output-001.gv, output-002.gv, etc. for each sentence. You can run dot to get image files (replace svg by the format you want):

dot -Tsvg output-001.gv > output-001.svg

The dot command comes with the graphviz program, which can be installed on Ubuntu with the following command:

sudo apt install graphviz

If you want to compile automatically with the -c switch, just adjust the output file extension to svg (or png, etc.) instead of gv:

python3 -o <output.svg> -c <input.conll>

This will get you output-001.svg, output-002.svg, etc. You can change the image format (png, etc.) with -f option:

python3 -o <output.png> -c -f png <input.conll>

Some corpora (as GSD) decompose French amalgams (for example "du" is decomposed to "de le"). The original word is saved within the conll file with a hyphen in the index:

1   Je  il  PRON    ...
2   vais    aller   VERB    ...
3   faire   faire   VERB    ...
4-5 du  _   ...
4   de  de  ADP ...
5   le  le  DET ...
6   vélo    vélo    NOUN    ...
7   cet ce  DET ...
8   après-midi  après-midi  NOUN    ...
9   .   .   PUNCT   ...

Use the --ignore-double-indices option to ignore these words:

python3 -o docs/french.svg -c testing/french.conll --ignore-double-indices

For more information, run:

python3 -h