=Paper=
{{Paper
|id=Vol-1625/abs1
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-1625/abs1.pdf
|volume=Vol-1625
}}
==None==
<pdf width="1500px">https://ceur-ws.org/Vol-1625/abs1.pdf</pdf>
<pre>
Verb-Noun Collocation and Government Model
       Extraction from Large Corpora

                 Vladislav Tushkanov, Oksana Dereza

        National Research University Higher School of Economics,
         v.tushkanov@outlook.com, oksana.dereza@gmail.com



  Abstract. Knowing the government model, or argument structure, of
  a verb is crucial for many NLP tasks. In this article, a method of auto-
  matic extraction of verbs from large annotated corpora is devised. This
  method allows to computationally efficiently extract government models
  and particular arguments for every verb using a simple window-based
  approach by iterating through each sentence with a window of fixed size
  and applying frequency filters to filter out noise.

  Keywords: collocations, verb government models, argument structure,
  corpus methods, parsing

</pre>