  Introduction. The area of natural language processing considers AI-complete
tasks that cannot be solved using traditional algorithmic actions. Such tasks
are commonly implemented with the usage of machine learning methodology and
means of computer linguistics. One of the preprocessing tasks of a text is the
search of noun phrases. The accuracy of this task has implications for the
effectiveness of many other tasks in the area of natural language processing.
In spite of the active development of research in the area of natural language
processing, the investigation of the search for noun phrases within Ukrainian
texts are still at an early stage. Results. The different methods of noun
phrases detection have been analyzed. The expediency of the representation of
sentences as a tree structure has been justified. The key disadvantage of many
methods of noun phrase detection is the severe dependence of the effectiveness
of their detection from the features of a certain language. Taking into account
the unified format of sentence processing and the availability of the trained
model for the building of sentence trees for Ukrainian texts, the Universal
Dependency model has been chosen. The complex method of noun phrases detection
in Ukrainian texts utilizing Universal Dependencies means and named-entity
recognition model has been suggested. Experimental verification of the
effectiveness of the suggested method on the corpus of Ukrainian news has been
performed. Different metrics of method accuracy have been calculated.
Conclusions. The results obtained can indicate that the suggested method can be
used to find noun phrases in Ukrainian texts. An accuracy increase of the
method can be made with the usage of appropriate named-entity recognition
models according to a subject area.
