PolEval is a SemEval-inspired evaluation campaign for natural language processing tools for Polish. Submitted tools compete against one another within certain tasks selected by organisers, using available data and are evaluated according to pre-established procedures.
PolEval 2018-related papers were presented at AI & NLP Workshop Day in Warsaw, Poland (October 19, 2018) and workshop proceedings were published by the Institute of Computer Science, Polish Academy of Sciences.
The proposed task consists in creating dependency parsers for Polish. Dependency parsers should be trained on trees from Polish Dependency Bank formatted according to the guidelines of Universal Dependency v2 (http://universaldependencies.org/guidelines.html). The task is open to everyone. Participants can take part in one of two subtasks or in both subtasks. We strongly encourage system developers from Poland and abroad to participate in the task.
Named entities (NE) are phrases that contain the names of things, such as persons, organizations and locations. Named Entity Recognition (NER) task is to label sequences of words in a text with appropriate named entity markup. Named entity recognition is an important task of information extraction systems.
A statistical language model is a probability distribution over sequences of words. Given a set of sentences in Polish in a random order, each with original punctuation, the goal of the task is to create a language model for Polish. Participants are allowed to use any approach to creating the model.