A Multilingual Named Entity Recognition System based on Fixed Ordinally-Forgetting Encoding
Allt fler tjänster idag erbjuder funktionalitet där fritext matas in och relevanta resultat returneras, vilket kräver identifiering av egennamn. Detta arbete utforskar en språkoberoende metod för att identifiera och returnera egennamn i text.This thesis describes a system whose goal is to find named entities in text. The system uses an encoding method, called the fixed ordinally-forgetting encoding, to efficiently encode variable-length text. We applied this encoding to words and characters and we used the resulting vectors as features. The system is language agnostic, and has been evaluated and tested on multiple languages. The syst