Planarized sentence representation for nested named entity recognition
R Geng, Y Chen, R Huang, Y Qin, Q Zheng - Information Processing & …, 2023 - Elsevier
One strategy to recognize nested entities is to enumerate overlapped entity spans for
classification. However, current models independently verify every entity span, which …
classification. However, current models independently verify every entity span, which …
Arc-nlp at multimodal hate speech event detection 2023: Multimodal methods boosted by ensemble learning, syntactical and entity features
Text-embedded images can serve as a means of spreading hate speech, propaganda, and
extremist beliefs. Throughout the Russia-Ukraine war, both opposing factions heavily relied …
extremist beliefs. Throughout the Russia-Ukraine war, both opposing factions heavily relied …
Tweets under the rubble: Detection of messages calling for help in earthquake disaster
The importance of social media is again exposed in the recent tragedy of the 2023 Turkey
and Syria earthquake. Many victims who were trapped under the rubble called for help by …
and Syria earthquake. Many victims who were trapped under the rubble called for help by …
Extraction and attribution of public figures statements for journalism in Indonesia using deep learning
News articles are usually written by journalists based on statements taken from interviews
with public figures. Attribution from such statements provides important information and it …
with public figures. Attribution from such statements provides important information and it …
[HTML][HTML] Evaluating Medical Entity Recognition in Health Care: Entity Model Quantitative Study
S Liu, A Wang, X Xiu, M Zhong, S Wu - JMIR Medical …, 2024 - medinform.jmir.org
Background: Named entity recognition (NER) models are essential for extracting structured
information from unstructured medical texts by identifying entities such as diseases …
information from unstructured medical texts by identifying entities such as diseases …
EPIC: An epidemiological investigation of COVID-19 dataset for Chinese named entity recognition
P Li, G Zhou, Y Guo, S Zhang, Y Jiang… - Information Processing & …, 2024 - Elsevier
Since the outbreak of COVID-19, it has had a huge impact on the whole world. In China,
there have been a large number of epidemiological investigation reports in response to …
there have been a large number of epidemiological investigation reports in response to …
ARC-NLP at PAN 2023: hierarchical long text classification for trigger detection
Fanfiction, a popular form of creative writing set within established fictional universes, has
gained a substantial online following. However, ensuring the well-being and safety of …
gained a substantial online following. However, ensuring the well-being and safety of …
ARC-NLP at CASE 2022 task 1: Ensemble learning for multilingual protest event detection
Automated socio-political protest event detection is a challenging task when multiple
languages are considered. In CASE 2022 Task 1, we propose ensemble learning methods …
languages are considered. In CASE 2022 Task 1, we propose ensemble learning methods …
ARC-NLP at ClimateActivism 2024: Stance and Hate Speech Detection by Generative and Encoder Models Optimized with Tweet-Specific Elements
Social media users often express hate speech towards specific targets and may either
support or refuse activist movements. The automated detection of hate speech, which …
support or refuse activist movements. The automated detection of hate speech, which …
[HTML][HTML] Balinese story texts dataset for narrative text analyses
Automatic narrative text analysis is gaining traction as artificial intelligence-based
computational linguistic tools such as named entity recognition systems and natural …
computational linguistic tools such as named entity recognition systems and natural …