Title: Automatically Annotated Turkish Corpus for Named Entity Recognition and Text Categorization using Large-Scale Gazetteers,
Abstract: Turkish Wikipedia Named-Entity Recognition and Text Categorization (TWNERTC)
dataset is a collection of automatically categorized and annotated sentences
obtained from Wikipedia. We constructed large-scale gazetteers by using a graph
crawler algorithm to extract relevant entity and domain information from a
semantic knowledge base, Freebase. The constructed gazetteers contains
approximately 300K entities with thousands of fine-grained entity types under
77 different domains. Since automated processes are prone to ambiguity, we also
introduce two new content specific noise reduction methodologies. Moreover, we
map fine-grained entity types to the equivalent four coarse-grained types:
person, loc, org, misc. Eventually, we construct six different dataset versions
and evaluate the quality of annotations by comparing ground truths from human
annotators. We make these datasets publicly available to support studies on
Turkish named-entity recognition (NER) and text categorization (TC).