In this paper, we describe a system by which the multilingual characteristics of Wikipedia can be utilized to annotate a large corpus of text with Named Entity Recognition (NER) t...
In this paper, we present HeiNER, the multilingual Heidelberg Named Entity Resource. HeiNER contains 1,547,586 disambiguated English Named Entities together with translations and ...
Wolodja Wentland, Johannes Knopp, Carina Silberer,...
We present a working Arabic information extraction (IE) system that is used to analyze large volumes of news texts every day to extract the named entity (NE) types person, organiz...
Wajdi Zaghouani, Bruno Pouliquen, Mohamed Ebrahim,...
Named Entity recognition (NER) is an important part of many natural language processing tasks. Current approaches often employ machine learning techniques and require supervised d...
Availability of labeled language resources, such as annotated corpora and domain dependent labeled language resources is crucial for experiments in the field of Natural Language ...