ProtagonistTagger -- a Tool for Entity Linkage of Persons in Texts from Various Languages and Domains

TL;DR

ProtagonistTagger is a multilingual tool designed for entity linkage of persons in texts, demonstrating high precision and recall across literary and news domains, enhancing semantic understanding of named entities.

Contribution

The paper introduces protagonistTagger, a novel tool for person NER and NED applicable across various languages and domains, with promising performance metrics.

Findings

Performance ranges between 78% and 88% in precision and recall.

Effective on texts from classic novels and online news.

Supports multiple languages, including English and Polish.

Abstract

Named entities recognition (NER) and disambiguation (NED) can add semantic context to the recognized named entities in texts. Named entity linkage in texts, regardless of a domain, provides links between the entities mentioned in unstructured texts and individual instances of real-world objects. In this poster, we present a tool - protagonistTagger - for person NER and NED in texts. The tool was tested on texts extracted from classic English novels and Polish Internet news. The tool's performance (both precision and recall) fluctuates between 78% and even 88%.