Named Entity Recognition (NER) models have been used in various contexts to automate the analysis of textual data, supporting tasks such as text categorization and relationship extraction across entities. While these models are typically trained on large corpora, their efficacy should be...

The main goal of this study is to build high-precision extractors for entities such as Person and Organization as a good initial seed that can be used for training and learning in machine-learning systems, for the same categories, other categories, and across domains, languages, and...

The main goal of this study is to build high-precision extractors for entities such as Person and Organization as a good initial seed that can be used for training and learning in machine-learning systems, for the same categories, other categories, and across domains, languages, and...