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Found 15 papers, 5 papers with code
Edition 1.2 of the PARSEME Shared Task on Semi-supervised Identification of Verbal Multiword Expressions
We present edition 1. 2 of the PARSEME shared task on identification of verbal multiword expressions (VMWEs).
ERMI at PARSEME Shared Task 2020: Embedding-Rich Multiword Expression Identification
This paper describes the ERMI system submitted to the closed track of the PARSEME shared task 2020 on automatic identification of verbal multiword expressions (VMWEs).
Overcoming the challenges in morphological annotation of Turkish in universal dependencies framework
This paper presents these issues and our proposals to more accurately represent morphosyntactic information for Turkish while adhering to guidelines of UD.
A Comprehensive Analysis of Static Word Embeddings for Turkish
There are basically two types of word embedding models which are non-contextual (static) models and contextual models.
Building Efficient and Effective OpenQA Systems for Low-Resource Languages
Our results show that SQuAD-TR makes OpenQA feasible for Turkish, which we hope encourages researchers to build OpenQA systems in other low-resource languages.
Incorporating Human Translator Style into English-Turkish Literary Machine Translation
We propose an approach based on stylistic features to evaluate the style of a translator in the output translations.
Enhancements to the BOUN Treebank Reflecting the Agglutinative Nature of Turkish
In this study, we aim to offer linguistically motivated solutions to resolve the issues of the lack of representation of null morphemes, highly productive derivational processes, and syncretic morphemes of Turkish in the BOUN Treebank without diverging from the Universal Dependencies framework.
Hierarchical Multitask Learning Approach for BERT
In this work, we adopt hierarchical multitask learning approaches for BERT pre-training.
Data and Representation for Turkish Natural Language Inference
In this paper, we offer a positive response for natural language inference (NLI) in Turkish.
Hierarchical Multi Task Learning with Subword Contextual Embeddings for Languages with Rich Morphology
In this study, we propose using subword contextual embeddings to capture the morphological information for languages with rich morphology.
Resources for Turkish Dependency Parsing: Introducing the BOUN Treebank and the BoAT Annotation Tool
In addition, we report the parsing results of a state-of-the-art dependency parser obtained over the BOUN Treebank as well as two other treebanks in Turkish.
Cultural Vocal Bursts Intensity Prediction
Dependency Parsing
A Hybrid Approach to Dependency Parsing: Combining Rules and Morphology with Deep Learning
Our first approach combines a state-of-the-art deep learning-based parser with a rule-based approach and the second one incorporates morphological information into the parser.
Generating Word and Document Embeddings for Sentiment Analysis
In this paper, we combine contextual and supervised information with the general semantic representations of words occurring in the dictionary.
Improving Named Entity Recognition by Jointly Learning to Disambiguate Morphological Tags
In this work, we propose a model which alleviates the need for such disambiguators by jointly learning NER and MD taggers in languages for which one can provide a list of candidate morphological analyses.
Dictionary-Based Concept Mining: An Application for Turkish
In this study, a dictionary-based method is used to extract expressive concepts from documents.
