Search Results for author: Daniel Dakota

Found 12 papers, 1 papers with code

Genres, Parsers, and BERT: The Interaction Between Parsers and BERT Models in Cross-Genre Constituency Parsing in English and Swedish

no code implementations EACL (AdaptNLP) 2021 Daniel Dakota

We perform a systematic set of experiments using two neural constituency parsers to examine how different parsers behave in combination with different BERT models with varying source and target genres in English and Swedish.

Constituency Parsing

Bidirectional Domain Adaptation Using Weighted Multi-Task Learning

1 code implementation ACL (IWPT) 2021 Daniel Dakota, Zeeshan Ali Sayyed, Sandra Kübler

In order to determine towhat degree the data imbalance between two domains and the domain differences affect results, we also carry out an experiment with two imbalanced in-domain treebanks and show that loss weighting also improves performance in an in-domain setting.

Domain Adaptation Multi-Task Learning

Investigating Multilingual Abusive Language Detection: A Cautionary Tale

no code implementations RANLP 2019 Kenneth Steimel, Daniel Dakota, Yue Chen, S K{\"u}bler, ra

Based on our findings, we can conclude that a multilingual optimization of classifiers is not possible even in settings where comparable data sets are used.

Abusive Language

Non-Deterministic Segmentation for Chinese Lattice Parsing

no code implementations RANLP 2017 Hai Hu, Daniel Dakota, S K{\"u}bler, ra

Parsing Chinese critically depends on correct word segmentation for the parser since incorrect segmentation inevitably causes incorrect parses.

Morphological Analysis

Towards Replicability in Parsing

no code implementations RANLP 2017 Daniel Dakota, S K{\"u}bler, ra

We investigate parsing replicability across 7 languages (and 8 treebanks), showing that choices concerning the use of grammatical functions in parsing or evaluation, the influence of the rare word threshold, as well as choices in test sentences and evaluation script options have considerable and often unexpected effects on parsing accuracies.

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