An overview of event extraction and its applications
J Liu, L Min, X Huang - arXiv preprint arXiv:2111.03212, 2021 - arxiv.org
With the rapid development of information technology, online platforms have produced
enormous text resources. As a particular form of Information Extraction (IE), Event Extraction …
enormous text resources. As a particular form of Information Extraction (IE), Event Extraction …
A survey on challenges and advances in natural language processing with a focus on legal informatics and low-resource languages
P Krasadakis, E Sakkopoulos, VS Verykios - Electronics, 2024 - mdpi.com
The field of Natural Language Processing (NLP) has experienced significant growth in
recent years, largely due to advancements in Deep Learning technology and especially …
recent years, largely due to advancements in Deep Learning technology and especially …
From dissonance to insights: Dissecting disagreements in rationale construction for case outcome classification
In legal NLP, Case Outcome Classification (COC) must not only be accurate but also
trustworthy and explainable. Existing work in explainable COC has been limited to …
trustworthy and explainable. Existing work in explainable COC has been limited to …
Knowledge mining and social dangerousness assessment in criminal justice: metaheuristic integration of machine learning and graph-based inference
One of the main challenges for computational legal research is drawing up innovative
heuristics to derive actionable knowledge from legal documents. While a large part of the …
heuristics to derive actionable knowledge from legal documents. While a large part of the …
Performance analysis of large language models in the domain of legal argument mining
Generative pre-trained transformers (GPT) have recently demonstrated excellent
performance in various natural language tasks. The development of ChatGPT and the …
performance in various natural language tasks. The development of ChatGPT and the …
Enhancing legal argument mining with domain pre-training and neural networks
The contextual word embedding model, BERT, has proved its ability on downstream tasks
with limited quantities of annotated data. BERT and its variants help to reduce the burden of …
with limited quantities of annotated data. BERT and its variants help to reduce the burden of …
Event detection with dual relational graph attention networks
J Mi, P Hu, P Li - … of the 29th International Conference on …, 2022 - aclanthology.org
Event detection, which aims to identify instances of specific event types from pieces of text, is
a fundamental task in information extraction. Most existing approaches leverage syntactic …
a fundamental task in information extraction. Most existing approaches leverage syntactic …
Can domain pre-training help interdisciplinary researchers from data annotation poverty? A case study of legal argument mining with BERT-based transformers
Abstract Interdisciplinary Natural Language Processing (NLP) research traditionally suffers
from the requirement for costly data annotation. However, transformer frameworks with pre …
from the requirement for costly data annotation. However, transformer frameworks with pre …
LexAbSumm: Aspect-based Summarization of Legal Decisions
TYS Santosh, M Aly, M Grabmair - arXiv preprint arXiv:2404.00594, 2024 - arxiv.org
Legal professionals frequently encounter long legal judgments that hold critical insights for
their work. While recent advances have led to automated summarization solutions for legal …
their work. While recent advances have led to automated summarization solutions for legal …
Research on the joint event extraction method orientates food live e-commerce
DH Mao, YM Liu, RX Li, JH Chen, YR Hao… - … Commerce Research and …, 2024 - Elsevier
In the evolving landscape of food e-commerce live streaming, the profusion of textual data,
marked by an excess of promotional vernacular and unstructured formats, presents a …
marked by an excess of promotional vernacular and unstructured formats, presents a …