Constructing a Named Entity Ontology from Web Corpora

This paper proposes a named entity (NE) ontology generation engine, called XNE-Tree engine, which produces relational named entities by given a seed. The engine incrementally extracts high co-occurring named entities with the seed by using a common search engine. In each iterative step, the seed will be replaced by its siblings or descendants, which form new seeds. In this way, XNE-Tree engine will build a tree structure with the original seed as a root incrementally. Two seeds, Chinese transliteration names of Nicole Kidman (a famous actress) and Ernest Hemingway (a famous writer), are experimented to evaluate the performance of the XNE-Tree. For test the applicability of the ontology, we employ it to a phoneme-character conversion system, which convert input phoneme syllable sequences to text strings. Total 100 Chinese transliteration names, including 50 person names and 50 location names are used as test data. We derive an ontology composed of 7,642 named entities. The results of phoneme-character conversion show that both the recall rate and the MRR are improved from 0.79 and 0.50 to 0.84 to 0.55, respectively.