Robust multilingual Named Entity Recognition with shallow semi-supervised features
نویسندگان
چکیده
منابع مشابه
Robust Multilingual Named Entity Recognition with Shallow Semi-Supervised Features
We present a multilingual Named Entity Recognition approach based on a robust and general set of features across languages and datasets. Our system combines shallow local information with clustering semi-supervised features induced on large amounts of unlabeled text. Understanding via empirical experimentation how to effectively combine various types of clustering features allows us to seamless...
متن کاملRobust Multilingual Named Entity Recognition with Shallow Semi-supervised Features (Extended Abstract)
We present a multilingual Named Entity Recognition approach based on a robust and general set of features across languages and datasets. Our system combines shallow local information with clustering semi-supervised features induced on large amounts of unlabeled text. Understanding via empirical experimentation how to effectively combine various types of clustering features allows us to seamless...
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The aim of Named Entity Recognition (NER) is to identify references of named entities in unstructured documents, and to classify them into pre-defined semantic categories. NER often aids from added background knowledge in the form of gazetteers. However using such a collection does not deal with name variants and cannot resolve ambiguities associated in identifying the entities in context and a...
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 2016
ISSN: 0004-3702
DOI: 10.1016/j.artint.2016.05.003