Entity Linking Based on Sentence Representation

Unsupervised Entity Linking with Abstract Meaning Representation

Most successful Entity Linking (EL) methods aim to link mentions to their referent entities in a structured Knowledge Base (KB) by comparing their respective contexts, often using similarity measures. While the KB structure is given, current methods have suffered from impoverished information representations on the mention side. In this paper, we demonstrate the effectiveness of Abstract Meanin...

Context Representation for Named Entity Linking

Named Entity Linking Based On Wikipedia

In this paper, we present the ideas and methodologies on labeling the mentioned entities with the wiki dataset. This paper presents a system for the recognition and semantic disambiguation of named entities based on information extracted from a large encyclopedic collection from Wikipedia. We focus on maximizing the similarity between the contextual information extracted from Wikipedia and the ...

Entity Linking with people entity on Wikipedia

This paper introduces a new model that uses named entity recognition, coreference resolution, and entity linking techniques, to approach the task of linking people entities on Wikipedia people pages to their corresponding Wikipedia pages if applicable. Our task is different from general and traditional entity linking because we are working in a limited domain, namely, people entities, and we ar...

Improvement of Chemical Named Entity Recognition through Sentence-based Random Under-sampling and Classifier Combination

Chemical Named Entity Recognition (NER) is the basic step for consequent information extraction tasks such as named entity resolution, drug-drug interaction discovery, extraction of the names of the molecules and their properties. Improvement in the performance of such systems may affects the quality of the subsequent tasks. Chemical text from which data for named entity recognition is extracte...