[PDF] Top 20 Named Entity Recognition for Novel Types by Transfer Learning

... NE types, we inspected the parameter matrix W t of the LR classifier in the step of learning type ...these types than the baseline Embed, which does not have a transfer learning ...to ... See full document

... a novel hierarchical prior struc- ture for supervised transfer learning in named entity recognition, motivated by the common structure of feature spaces for this task across ... See full document

... first Named Entity Recognition (NER) task to recognize chemical and protein entities from Spanish biomedical ...of transfer learning with language models, we in- troduce the BERT ... See full document

... of named entity recog- nition (NER) from electronic medical records, which is one of the most fundamental and critical problems for medical text ...double transfer learning framework (La- DTL) ... See full document

... our transfer learning setting is that the two datasets we used have almost identical samples and only differ in their ...10 entity classes: com- pany, facility, Geo location, movie, music artist, ... See full document

... We present experimental results on external, i.e. publicly available, corpora, as well as on internally gathered large-scale real-world datasets. First, a deep neural network model is developed for NER, and we ... See full document

... two transfer strategies have their own advantages over each other in dif- ferent situations, which is largely ignored by ex- isting ...adversarial learning, i.e., GRAD and AT, into one transfer ... See full document

... supervised learning, which is the scenario we explore here, recent methods include: feature augmentation (Daum´e III, 2007; Arnold et ...in transfer learning (also known as domain adaptation) that ... See full document

... supervised learning is used, the availability of a large collection of annotated data is a ...unsupervised learning techniques that promise fast deployment for many entity types without the ... See full document

... many named entity ...consider named entity types such as gene, virus and disease, because of the large (and growing) number of names in use, the fact that the names are heavily ... See full document

... of named entities in a text and classify- ing them with predefined types such as person, lo- cation and ...which entity a particular mention refers to, by assigning a knowledge base entity ... See full document

... As with the majority of tasks in contemporary nat- ural language processing, most approaches to NER have been based on supervised machine learning. However, although resources for a handful of lan- guages have ... See full document

... Arabic Named Entity Recognition system was developed by Benajiba and Rosso [32] who have developed an ANER system, ANERsys ...various types of NEs, among them, are Person, Location, and ... See full document

... a novel solution for the Arabic NER problem, and handling specialised NE ...new types of NEs and does not generate problems typical of supervised methods that require annotated training data, and demand ... See full document

... proactive learning has been proposed to model dif- ferent types of experts (Donmez and Carbonell, 2008, ...Proactive learning assumes that (1) not all annotators are perfect, but that there is at ... See full document

... Papers on NER for English language commonly use publicly available named entity tagged corpora for system development and evaluation (Tjong Kim Sang and De Meulder, 2003; Chinchor, 1998). As no such ... See full document

... with 36 different kinds of biological entities, and with parts of speech. Previous NER work using this corpus has employed 10-fold cross-validation for evaluation. We wanted to explore different model variations (e.g., ... See full document

... Not much work has been done in NER in Telugu and other Indian languages so far. In this paper, we have reported our work on Named Entity Recogni- tion for Telugu. We have developed a CRF based noun tagger, ... See full document

... Since there is no study on active learning for NER task previously, we only introduce general active learning methods here. Many existing active learn- ing methods are to select the most uncertain exam- ... See full document

... e.g., named entity recognition. Segment-based known as entity recognition methods achieve much better correctness than the word- based alternative ... See full document