This is the official repository of the Resume Corpus dataset, a meticulously curated collection designed specifically for advancing research and applications in Named Entity Recognition (NER). This dataset is a valuable asset for machine learning practitioners, data scientists, and NER enthusiasts, offering:
- Extensive Coverage: Encompassing a wide array of resumes across various industries and roles, providing a diverse and comprehensive dataset for robust model training.
- Rich Annotation:Each resume is annotated with 36 distinct entities, including personal information, educational background, professional experience, skills, and more. This rich annotation facilitates the development of sophisticated NER models capable of recognizing a wide range of entities.
- Real-World Application:Tailored to address the complexities and nuances of real-world resumes, making it an ideal resource for developing practical NER solutions in recruitment, talent management, and career development.
- Open Access:Freely accessible for academic and research purposes, promoting innovation and collaboration in the field of NER.
