Although Indonesian is known to be the fourth most frequently used language over the
internet, the research progress on this language in the natural language processing (NLP) is …

Deep learning-based language models pretrained on large unannotated text corpora have
been demonstrated to allow efficient transfer learning for natural language processing, with …

Every year, the Conference on Computational Natural Language Learning (CoNLL) features
a shared task, in which participants train and test their learning systems on the same data …

In this paper we describe the TurkuNLP entry at the CoNLL 2018 Shared Task on
Multilingual Parsing from Raw Text to Universal Dependencies. Compared to the last year …

We propose a novel neural network model for joint part-of-speech (POS) tagging and
dependency parsing. Our model extends the well-known BIST graph-based dependency …

We introduce Rosita, a method to produce multilingual contextual word representations by
training a single language model on text from multiple languages. Our method combines the …

We recast dependency parsing as a sequence labeling problem, exploring several
encodings of dependency trees as labels. While dependency parsing by means of …

We present experiments on Slovenian, Croatian and Serbian morphosyntactic annotation
and lemmatisation between the former state-of-the-art for these three languages and one of …

In this paper, we present a novel lemmatization method based on a sequence-to-sequence
neural network architecture and morphosyntactic context representation. In the proposed …

We present a new manually annotated corpus for broad-coverage named entity recognition
for Finnish. Building on the original Universal Dependencies Finnish corpus of 754 …