Classification task is an integral part of named entity recognition system to classify a recognized named entity to its corresponding class. This task has not received much attention in the biomedical domain, due to the lack of awareness to differentiate feature sources and strategies in previous studies. In this research, we analyze different sources and strategies of protein name classificati...

Name identification has been worked on quite intensively for the past few years, and has been incorporated into several products revolving around natural language processing tasks. Many researchers have attacked the name identification problem in a variety of languages, but only a few limited research efforts have focused on named entity recognition for Arabic script. This is due to the lack of...

We explored a new approach to named entity recognition based on hundreds of machine learning models, each trained to distinguish a single entity, and showed its application to gene name identification (GNI). The rationale for our approach, which we named “one model per entity” (OMPE), was that increasing the number of models would make the learning task easier for each individual model. Our tra...

Internet can be seen as a network of peers that store digital representations of entities from the real world (e.g., person, locations, events). Different peers locally represent different “versions” (i.e., different points of view) of the same real world entity. In these different versions, entities are normally identified by multiple (possibly different) names. We propose a distributed entity...

Name entity recognition is an essential task in extracting biological knowledge. In biological corpus, protein names and other terminologies are mixed in natural language sentences. Sometimes whether an abbreviation is a protein name or not depends on the context. Protein names are often composed of gene names, cell names, or even drug names. Moreover, the number of newly coined protein names i...

ContentModel : NamedElement web -> Web + ownedEntityModel->EntityModel? abstract Web : NamedElement ownedList : List * ownedWeb : Web *Web : NamedElement ownedList : List * ownedWeb : Web * abstract List : NamedElement contentTypes -> ContentType * xor Type Library ListList : NamedElement contentTypes -> ContentType * xor Type Library List abstract ContentType : NamedElement isAbstract : intege...

To recognize instances of medical information concerning prostate cancer and its relevant genes, we developed a machine learning-based relation recognizer using rich contextual features. We collected prostate cancer-related abstracts from Medline. We then constructed an annotated corpus of prostate cancer and gene relations, which consisted of six topic − classified categories, with more detail...

Much work has already been done on building named entity recognition systems. However most of this work has been concentrated on English and other European languages. Hence, building a named entity recognition (NER) system for South Asian Languages (SAL) is still an open problem because they exhibit characteristics different from English. This paper builds a named entity recognizer which also i...

Name entity recognition (NER) is the foundation of a wide range natural language processing (NLP) task in domain test identification. In this paper, we continue to train pre-trained BERT model by unlabeled texts related identification, so as inject knowledge into and realize adaptation. The experiment results show that proposed domain-adaptive pre-training method increases F1 value 1% compared ...

This paper presents an approach to integrating functions for both transcription and named entity (NE) identification into a large vocabulary continuous speech recognition system. It builds on NE tagged language modelling approach, which was recently applied for development of the statistical NE annotation system. We also present results for proper name identification experiment using the Hub-4 ...