1 citations · 2 across the 4 of their papers we have counts for
4 papers
Utilizing Large Language Models for Named Entity Recognition in Traditional Chinese Medicine against COVID-19 Literature: Comparative Study
Xu Tong, Nina Smirnova, Sharmila Upadhyaya +5
Objective: To explore and compare the performance of ChatGPT and other state-of-the-art LLMs on domain-specific NER tasks covering different entity types and domains in TCM against…
Enhancing Software-Related Information Extraction via Single-Choice Question Answering with Large Language Models
Wolfgang Otto, Sharmila Upadhyaya, Stefan Dietze
This paper describes our participation in the Shared Task on Software Mentions Disambiguation (SOMD), with a focus on improving relation extraction in scholarly texts through gener…
Toward FAIR Semantic Publishing of Research Dataset Metadata in the Open Research Knowledge Graph
Raia Abu Ahmad, Jennifer D'Souza, Matthäus Zloch +5
Search engines these days can serve datasets as search results. Datasets get picked up by search technologies based on structured descriptions on their official web pages, informed…
GSAP-NER: A Novel Task, Corpus, and Baseline for Scholarly Entity Extraction Focused on Machine Learning Models and Datasets
Wolfgang Otto, Matthäus Zloch, Lu Gan +2
Named Entity Recognition (NER) models play a crucial role in various NLP tasks, including information extraction (IE) and text understanding. In academic writing, references to mac…