Unsupervised Named Entity Recognition Using Syntactic and Semantic Contextual Evidence

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Unsupervised Named Entity Recognition Using Syntatic and Semantic Contextual Evidence

Proper nouns form an open class, making the incompleteness of manually or automatically learned classification rules an obvious problem. The purpose of this paper is twofold:first, to suggest the use of a complementary "backup" method to increase the robustness of any hand-crafted or machinelearning-based NE tagger; and second, to explore the effectiveness of using more fine-grained evidence--n...

متن کامل

Language Independent Named Entity Recognition Combining Morphological and Contextual Evidence

Identifying and classifying personal, geographic, institutional or other names in a text is an important task for numerous applications. This paper describes and evaluates a language-independent bootstrapping algorithm based on iterative learning and re-estimation of contextual and mOrphological patterns captured in hierarchically smoothed trie models. The algorithm learns from unannotated text...

متن کامل

Language Independent Named Entity Recognition Combining Morphological and Contextual Evidence

Identifying and classifying personal, geographic, institutional or other names in a text is an important task for numerous applications. This paper describes and evaluates a language-independent bootstrapping algorithm based on iterative learning and re-estimation of contextual and mOrphological patterns captured in hierarchically smoothed trie models. The algorithm learns from unannotated text...

متن کامل

Named Entity Recognition in Persian Text using Deep Learning

Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Computational Linguistics

سال: 2001

ISSN: 0891-2017,1530-9312

DOI: 10.1162/089120101300346822