Separating Named Entities

Varování

Publikace nespadá pod Ekonomicko-správní fakultu, ale pod Filozofickou fakultu. Oficiální stránka publikace je na webu muni.cz.
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ULIPOVÁ Barbora GRÁC Marek

Rok publikování 2014
Druh Článek ve sborníku
Konference Eighth Workshop on Recent Advances in Slavonic Natural Language Processing
Fakulta / Pracoviště MU

Filozofická fakulta

Citace
www https://nlp.fi.muni.cz/raslan/2014/15.pdf
Obor Jazykověda
Klíčová slova text corpus; mutual information; named entities
Popis In this paper, we analyze the situation of long sequences of mostly capitalized words which look like a named entity but in fact they consist of several named entities. An example of such phenomena is hokejista (hockey player) New York Rangers Jaromír Jágr. Without splitting the sequence correctly, we will wrongly assume that the whole capitalized sequence is a name of the hockey player. To find out how the sequence should be split into the correct named entities, we tested several methods. These methods are based on the frequencies of the words they consist of and their n-grams. The method DIFF-2 proposed in this article obtained much better results than MI-score or logDice.
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