We present a new method for detecting and disambiguating named entities in open domain text. A disambiguation SVM kernel is trained to exploit the high coverage and rich structure of the knowledge encoded in an online encyclopedia. The resulting model significantly outperforms a less informed baseline.
In another supervised approach, REF solve name disambiguation by designing and training a disambiguation SVM kernel that exploits the high coverage and rich structure of the knowledge encoded in an online encyclopedia.
Using Encyclopedic Knowledge For Named Entity Disambiguation
Conference Of The European Association For Computational Linguistics
Computer Science