Following the interest taken into Name Entity Recognition in academic literature in the Gene Mention recognition task of BioCreative I and II, the BioCreative IV hopes to make the implementation of the system in the field of detecting mentions of chemical compounds and drugs. Considering that the machine learning methods have obtained great success in the correct identification of gene and prot...

Named entity recognition, as a sub-task of information extraction, has attracted widespread attention from scholars at home and abroad since it was proposed, series studies discussions have been carried out based on it. This paper discusses the existing named recognition technology its history development.

Using low dimensional vector space to represent words has been very effective in many NLP tasks. However, it doesn't work well when faced with the problem of rare and unseen words. In this paper, we propose to leverage the knowledge in semantic dictionary in combination with some morphological information to build an enhanced vector space. We get an improvement of 2.3% over the state-of-the-art...

This paper focuses on the creation of Arabic named entity gazetteers, by exploiting Wikipedia and using the Naïve Bayes classifier to classify the named entities into the three main categories: person, location, and organization. The process of building the gazetteer starts with automatically creating the datasets. The dataset for the training is constructed using only Arabic text, whereas, the...

Person Name Recognition from transcriptions of TV shows spoken content is a crucial step towards multimedia document indexing. Recognizing Person Names implies the combination of three main modules: Automatic Speech Recognition, NamedEntity Recognition and Entity Linking to associate the recognized surface form to a normalized Person Name. The three modules are potentially error prone. Hence, b...

Linking entities with knowledge base (entity linking) is a key issue in bridging the textual data with the structural knowledge base. Due to the name variation problem and the name ambiguity problem, the entity linking decisions are critically depending on the heterogenous knowledge of entities. In this paper, we propose a generative probabilistic model, called entitymention model, which can le...

This paper reports about the development of a Named Entity Recognition (NER) system in two leading Indian languages, namely Bengali and Hindi using the Maximum Entropy (ME) framework. We have used the annotated corpora, obtained from the IJCNLP-08 NER Shared Task on South and South East Asian Languages (NERSSEAL) and tagged with a fine-grained Named Entity (NE) tagset of twelve tags. An appropr...