38 citations · 117 across the 22 of their papers we have counts for
7 papers · 1 filter
ÚFAL MRPipe at MRP 2019: UDPipe Goes Semantic in the Meaning Representation Parsing Shared Task
Milan Straka, Jana Straková
We present a system description of our contribution to the CoNLL 2019 shared task, Cross-Framework Meaning Representation Parsing (MRP 2019). The proposed architecture is our first…
Grammatical Error Correction in Low-Resource Scenarios
Jakub Náplava, Milan Straka
Grammatical error correction in English is a long studied problem with many existing systems and datasets. However, there has been only a limited research on error correction of ot…
CUNI System for the Building Educational Applications 2019 Shared Task: Grammatical Error Correction
Jakub Náplava, Milan Straka
In this paper, we describe our systems submitted to the Building Educational Applications (BEA) 2019 Shared Task (Bryant et al., 2019). We participated in all three tracks. Our mod…
Czech Text Processing with Contextual Embeddings: POS Tagging, Lemmatization, Parsing and NER
Milan Straka, Jana Straková, Jan Hajič
Contextualized embeddings, which capture appropriate word meaning depending on context, have recently been proposed. We evaluate two meth ods for precomputing such embeddings, BERT…
Evaluating Contextualized Embeddings on 54 Languages in POS Tagging, Lemmatization and Dependency Parsing
Milan Straka, Jana Straková, Jan Hajič
We present an extensive evaluation of three recently proposed methods for contextualized embeddings on 89 corpora in 54 languages of the Universal Dependencies 2.3 in three tasks:…
UDPipe at SIGMORPHON 2019: Contextualized Embeddings, Regularization with Morphological Categories, Corpora Merging
Milan Straka, Jana Straková, Jan Hajič
We present our contribution to the SIGMORPHON 2019 Shared Task: Crosslinguality and Context in Morphology, Task 2: contextual morphological analysis and lemmatization. We submitted…
Neural Architectures for Nested NER through Linearization
Jana Straková, Milan Straka, Jan Hajič
We propose two neural network architectures for nested named entity recognition (NER), a setting in which named entities may overlap and also be labeled with more than one label. W…