Sentence segmentation
19 papers with code • 1 benchmarks • 3 datasets
Latest papers with no code
GujiBERT and GujiGPT: Construction of Intelligent Information Processing Foundation Language Models for Ancient Texts
In the context of the rapid development of large language models, we have meticulously trained and introduced the GujiBERT and GujiGPT language models, which are foundational models specifically designed for intelligent information processing of ancient texts.
Sentence Identification with BOS and EOS Label Combinations
To tackle this issue, we formulate a novel task of sentence identification, where the goal is to identify SUs while excluding NSUs in a given text.
Mukayese: Turkish NLP Strikes Back
As a solution, we present Mukayese, a set of NLP benchmarks for the Turkish language that contains several NLP tasks.
Transformer-Encoder-GRU (T-E-GRU) for Chinese Sentiment Analysis on Chinese Comment Text
Chinese sentiment analysis (CSA) has always been one of the challenges in natural language processing due to its complexity and uncertainty.
TGIF: Tree-Graph Integrated-Format Parser for Enhanced UD with Two-Stage Generic- to Individual-Language Finetuning
We present our contribution to the IWPT 2021 shared task on parsing into enhanced Universal Dependencies.
Sentiment Analysis for Troll Detection on Weibo
We employ the resulting techniques to develop and test a sentiment analysis approach for troll detection, based on a variety of machine learning strategies.
Experiments on transfer learning architectures for biomedical relation extraction
Relation extraction (RE) consists in identifying and structuring automatically relations of interest from texts.
When Classical Chinese Meets Machine Learning: Explaining the Relative Performances of Word and Sentence Segmentation Tasks
We consider three major text sources about the Tang Dynasty of China in our experiments that aim to segment text written in classical Chinese.
The AFRL IWSLT 2020 Systems: Work-From-Home Edition
This report summarizes the Air Force Research Laboratory (AFRL) submission to the offline spoken language translation (SLT) task as part of the IWSLT 2020 evaluation campaign.
A Latent Topic Modeling approach for Subject Summarization of Research on the Military Art and Science in South Korea
Within the military art and science research articles, many of studies have focused on the empirical examination or theoretically review interests related to military phenomena (e. g., military power, security relations).