Character Feature Learning for Named Entity Recognition
نویسندگان
چکیده
منابع مشابه
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 کاملExploiting Feature Hierarchy for Transfer Learning in Named Entity Recognition
We present a novel hierarchical prior structure for supervised transfer learning in named entity recognition, motivated by the common structure of feature spaces for this task across natural language data sets. The problem of transfer learning, where information gained in one learning task is used to improve performance in another related task, is an important new area of research. In the subpr...
متن کاملNamed Entity Recognition with Character-Level Models
We discuss two named-entity recognition models which use characters and character -grams either exclusively or as an important part of their data representation. The first model is a character-level HMM with minimal context information, and the second model is a maximum-entropy conditional markov model with substantially richer context features. Our best model achieves an overall F of 86.07% on...
متن کاملCharNER: Character-Level Named Entity Recognition
We describe and evaluate a character-level tagger for language-independent Named Entity Recognition (NER). Instead of words, a sentence is represented as a sequence of characters. The model consists of stacked bidirectional LSTMs which inputs characters and outputs tag probabilities for each character. These probabilities are then converted to consistent word level named entity tags using a Vit...
متن کاملSingle Character Chinese Named Entity Recognition
Single character named entity (SCNE) is a name entity (NE) composed of one Chinese character, such as “ ” (zhong1, China) and “ ” e2,Russia . SCNE is very common in written Chinese text. However, due to the lack of in-depth research, SCNE is a major source of errors in named entity recognition (NER). This paper formulates the SCNE recognition within the sourcechannel model framework. Our experi...
متن کاملذخیره 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: IEICE Transactions on Information and Systems
سال: 2018
ISSN: 0916-8532,1745-1361
DOI: 10.1587/transinf.2017kbl0001