Abstract: The traditional data annotation process is often labor-intensive, time-consuming, and susceptible to human bias, which complicates the management of increasingly complex datasets. This study ...

AI models require well-labeled data to achieve high accuracy. Without structured datasets, they struggle with precision, bias, and real-world reliability. Data annotation companies lay the foundation ...

Code for the project Plant Science Knowledge Graph Corpus: a gold standard entity and relation corpus for the molecular plant sciences. To cite this project: @article ...

Automated text annotation is a compelling use case for generative large language models (LLMs) in social media research. Recent work suggests that LLMs can achieve strong performance on annotation ...

Artificial intelligence has transformed code generation, with large language models (LLMs) for code now integral to software engineering. These models support code synthesis, debugging, and ...

We publish deeply researched (and often vastly underread) academic papers about our collective omnipresent media bias. We publish deeply researched (and often vastly underread) academic papers about ...

Managing and validating structured data efficiently poses a significant challenge in today’s digital age. Traditional methods of function calling or JSON schema validation often fall short, especially ...

Abstract: Creating rich semantic text annotations is a complex process that involves combining multiple natural-language annotation approaches. This annotation process is often approached sequentially ...

When my son, Ian, was 3, I bought him a cellphone. It had three buttons: "Call Mom," "Call Dad" and "Call Grandma." He was young, but it helped us feel better he could reach us in case of an emergency ...