A comprehensive survey on relation extraction: Recent advances and new frontiers
Relation extraction (RE) involves identifying the relations between entities from underlying
content. RE serves as the foundation for many natural language processing (NLP) and …
content. RE serves as the foundation for many natural language processing (NLP) and …
A large language model for electronic health records
There is an increasing interest in developing artificial intelligence (AI) systems to process
and interpret electronic health records (EHRs). Natural language processing (NLP) powered …
and interpret electronic health records (EHRs). Natural language processing (NLP) powered …
Document-level relation extraction with adaptive focal loss and knowledge distillation
Document-level Relation Extraction (DocRE) is a more challenging task compared to its
sentence-level counterpart. It aims to extract relations from multiple sentences at once. In …
sentence-level counterpart. It aims to extract relations from multiple sentences at once. In …
Gatortron: A large clinical language model to unlock patient information from unstructured electronic health records
There is an increasing interest in developing artificial intelligence (AI) systems to process
and interpret electronic health records (EHRs). Natural language processing (NLP) powered …
and interpret electronic health records (EHRs). Natural language processing (NLP) powered …
Webformer: The web-page transformer for structure information extraction
Structure information extraction refers to the task of extracting structured text fields from web
pages, such as extracting a product offer from a shopping page including product title …
pages, such as extracting a product offer from a shopping page including product title …
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 …
A sequence-to-sequence approach for document-level relation extraction
Motivated by the fact that many relations cross the sentence boundary, there has been
increasing interest in document-level relation extraction (DocRE). DocRE requires …
increasing interest in document-level relation extraction (DocRE). DocRE requires …
DREEAM: Guiding attention with evidence for improving document-level relation extraction
Document-level relation extraction (DocRE) is the task of identifying all relations between
each entity pair in a document. Evidence, defined as sentences containing clues for the …
each entity pair in a document. Evidence, defined as sentences containing clues for the …
KPI-BERT: A joint named entity recognition and relation extraction model for financial reports
L Hillebrand, T Deußer, T Dilmaghani… - 2022 26th …, 2022 - ieeexplore.ieee.org
We present KPI-BERT, a system which employs novel methods of named entity recognition
(NER) and relation extraction (RE) to extract and link key performance indicators (KPIs), eg" …
(NER) and relation extraction (RE) to extract and link key performance indicators (KPIs), eg" …
[PDF][PDF] Hacred: A large-scale relation extraction dataset toward hard cases in practical applications
Relation extraction (RE) is an essential topic in natural language processing and has
attracted extensive attention. Current RE approaches achieve fantastic results on common …
attracted extensive attention. Current RE approaches achieve fantastic results on common …