  In this paper we describe our submissions to the 2nd and 3rd SlavNER Shared
Tasks held at BSNLP 2019 and BSNLP 2021, respectively. The tasks focused on the
analysis of Named Entities in multilingual Web documents in Slavic languages
with rich inflection. Our solution takes advantage of large collections of both
unstructured and structured documents. The former serve as data for
unsupervised training of language models and embeddings of lexical units. The
latter refers to Wikipedia and its structured counterpart - Wikidata, our
source of lemmatization rules, and real-world entities. With the aid of those
resources, our system could recognize, normalize and link entities, while being
trained with only small amounts of labeled data.
