In this paper, we present a simple yet novel method of exploiting unlabeled text to further improve the accuracy of a high-performance state-of-theart named entity recognition (NER) system. The method utilizes the empirical property that many named entities occur in one name class only. Using only unlabeled text as the additional resource, our improved NER system achieves an F1 score of 87.13%,...

We have developed a new OSGi-based platform for Named Entity Recognition (NER) which uses a voting strategy to combine the results produced by several existing NER systems (currently OpenNLP, LingPipe and Stanford). The different NER systems have been systematically decomposed and modularized into the same pipeline of preprocessing components in order to support a flexible selection and orderin...

This paper mainly describes a Chinese named entity recognition (NER) system NER@ISCAS, which integrates text, partof-speech and a small-vocabularycharacter-lists feature and heristic postprocess rules for MSRA NER open track under the framework of Conditional Random Fields (CRFs) model.

Named Entity Recognition (NER) is an important preprocessing tool for many Natural Language Processing tasks like Information Retrieval, Question Answering or Machine Translation. This paper is focused on NER for Czech language. The proposed NER is based on knowledge and experiences acquired on other languages and adapted for Czech. Our recognizer outperforms the previously introduced recognize...

The task of Named Entity Recognition (NER) is to identify in text predefined units of information such as person names, organizations and locations. In this work, we address the problem of NER in Estonian using supervised learning approach. We explore common issues related to building a NER system such as the usage of language-agnostic and languagespecific features, the representation of named ...

CC-BY-NC-ND 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was. Abstract The rates at which lesions are removed by DNA repair can vary widely throughout the genome with important implications for genomic stability. To study this, we measured the distribution of nucleotide excision repair (NER) rates f...

Nucleotide excision repair (NER) is a major DNA repair pathway in eukaryotic cells. NER removes structurally diverse lesions such as pyrimidine dimers, arising upon UV irradiation or bulky chemical adducts, arising upon exposure to carcinogens and some chemotherapeutic drugs. NER defects lead to three genetic disorders that result in predisposition to cancers, accelerated aging, neurological an...

Current text-based question answering (QA) systems usually contain a named entity recogniser (NER) as a core component. Named entity recognition has traditionally been developed as a component for information extraction systems, and current techniques are focused on this end use. However, no formal assessment has been done on the characteristics of a NER within the task of question answering. I...

We present the first known result for named entity recognition (NER) in realistic largevocabulary spoken Chinese. We establish this result by applying a maximum entropy model, currently the single best known approach for textual Chinese NER, to the recognition output of the BBN LVCSR system on Chinese Broadcast News utterances. Our results support the claim that transferring NER approaches from...