UWB at SemEval-2016 Task 1: Semantic Textual Similarity using Lexical, Syntactic, and Semantic Information
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016) (2016)
We present our UWB system for Semantic
Textual Similarity (STS) task at SemEval
2016. Given two sentences, the system estimates
the degree of their semantic similarity.
We use state-of-the-art algorithms for the
meaning representation and combine them
with the best performing approaches to STS
from previous years. These methods benefit
from various sources of information, such as
lexical, syntactic, and semantic.
In the monolingual task, our system achieve
mean Pearson correlation 75.7% compared
with human annotators. In the cross-lingual
task, our system has correlation 86.3% and is
ranked first among 26 systems.