Overview of Named Entity Recognition

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...

Arabic Named Entity Recognition

Stemming is the process of reducing words to their stems or roots. Due to the morphological richness and complexity of the Arabic language, stemming is an essential part of most Natural Language Processing (NLP) tasks for this language. In this paper, we study the impact of different stemming approaches on the Named Entity Recognition (NER) task for Arabic and explore the merits, limitations an...

Named Entity Recognition Approaches

Recognizing and extracting exact name entities, like Persons, Locations and Organizations are very useful to mining information from text. Learning to extract names in natural language text is called Named Entity Recognition (NER) task. Proper named entity recognition and extraction is important to solve most problems in hot research area such as Question Answering and Summarization Systems, In...

Nested Named Entity Recognition

Many named entities contain other named entities inside them. Despite this fact, the field of named entity recognition has almost entirely ignored nested named entity recognition, but due to technological, rather than ideological reasons. In this paper, we present a new technique for recognizing nested named entities, by using a discriminative constituency parser. To train the model, we transfo...

Named Entity Recognition