Dialogue Evaluation 2023


Sentiment Analysis for Named Entities in News Texts

The shared task and the paper submission are over. Thank you all for participating!


Key dates

  • 26 December — publication of the train data;
  • 4 March — publication of the test data;
  • 10 March — submission of the results;
  • 13 March — results of the competition;
  • 8 April — paper submission deadline.


Sentiment analysis, i.e. identification of opinions on the subject discussed in the text, is one of the most actively developing applications of natural language processing.

Sentiment analysis of news texts is an important direction in the field of opinion analysis, since the detection and tracking of sentiment trends in the news flow is important for building various kinds of analytical systems, tracking the image in the media of specific people or companies.

Sentiment in relation to entity in a news text can come from at least three different sources:

  • opinion of the author of the text,
  • cited opinion, while the carrier of the opinion may or may not be mentioned in the text,
  • an implicit opinion that follows from any of the actions or reactions mentioned, for example, X fired Y.. Such information is often present even in an apparently neutral account of events.


We invite participants to solve the problem of extracting sentiments of three classes (negative, positive, neutral) from news texts in relation to pre-marked entities such as PERSON, ORGANIZATION, PROFESSION, COUNTRY, NATIONALITY within a separate sentence.