Natural language processing in law: Prediction of outcomes in the higher courts of Turkey
Natural language processing (NLP) based approaches have recently received attention for
legal systems of several countries. It is of interest to study the wide variety of legal systems …
legal systems of several countries. It is of interest to study the wide variety of legal systems …
A Finnish news corpus for named entity recognition
T Ruokolainen, P Kauppinen, M Silfverberg… - Language Resources …, 2020 - Springer
We present a corpus of Finnish news articles with a manually prepared named entity
annotation. The corpus consists of 953 articles (193,742 word tokens) with six named entity …
annotation. The corpus consists of 953 articles (193,742 word tokens) with six named entity …
Named-entity recognition in Turkish legal texts
C Çetindağ, B Yazıcıoğlu, A Koç - Natural Language Engineering, 2023 - cambridge.org
Natural language processing (NLP) technologies and applications in legal text processing
are gaining momentum. Being one of the most prominent tasks in NLP, named-entity …
are gaining momentum. Being one of the most prominent tasks in NLP, named-entity …
An evaluation of recent neural sequence tagging models in Turkish named entity recognition
Named entity recognition (NER) is an extensively studied task that extracts and classifies
named entities in a text. NER is crucial not only in downstream language processing …
named entities in a text. NER is crucial not only in downstream language processing …
Abstractive text summarization and new large-scale datasets for agglutinative languages Turkish and Hungarian
Due to the exponential growth in the number of documents on the Web, accessing the
salient information relevant to a user need is gaining importance, which increases the …
salient information relevant to a user need is gaining importance, which increases the …
A Twitter Corpus for named entity recognition in Turkish
B Çarık, R Yeniterzi - … of the Thirteenth Language Resources and …, 2022 - aclanthology.org
This paper introduces a new Turkish Twitter Named Entity Recognition dataset. The dataset,
which consists of 5000 tweets from a year-long period, was labeled by multiple annotators …
which consists of 5000 tweets from a year-long period, was labeled by multiple annotators …
Enhancing deep neural networks with morphological information
M Klemen, L Krsnik, M Robnik-Šikonja - Natural Language …, 2023 - cambridge.org
Deep learning approaches are superior in natural language processing due to their ability to
extract informative features and patterns from languages. The two most successful neural …
extract informative features and patterns from languages. The two most successful neural …
TurkishDelightNLP: A neural Turkish NLP toolkit
We introduce a neural Turkish NLP toolkit called TurkishDelightNLP that performs
computational linguistic analyses from morphological level to semantic level that involves …
computational linguistic analyses from morphological level to semantic level that involves …
ERMI at PARSEME shared task 2020: Embedding-rich multiword expression identification
Z Yirmibeşoğlu, T Güngör - Proceedings of the Joint Workshop on …, 2020 - aclanthology.org
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) …
shared task 2020 on automatic identification of verbal multiword expressions (VMWEs) …
mgsohrab at wnut 2020 shared task-1: Neural exhaustive approach for entity and relation recognition over wet lab protocols
We present a neural exhaustive approach that addresses named entity recognition (NER)
and relation recognition (RE), for the entity and re-lation recognition over the wet-lab …
and relation recognition (RE), for the entity and re-lation recognition over the wet-lab …