Named Entity Recognition (NER) is a key component in NLP systems for question
answering, information retrieval, relation extraction, etc. NER systems have been studied …

Transformer-based pretrained language models (PLMs) have started a new era in modern
natural language processing (NLP). These models combine the power of transformers …

Language models pretrained on text from a wide variety of sources form the foundation of
today's NLP. In light of the success of these broad-coverage models, we investigate whether …

Motivation Biomedical text mining is becoming increasingly important as the number of
biomedical documents rapidly grows. With the progress in natural language processing …

A bottleneck in efficiently connecting new materials discoveries to established literature has
arisen due to an increase in publications. This problem may be addressed by using named …

Abstract PubTator Central (https://www. ncbi. nlm. nih. gov/research/pubtator/) is a web
service for viewing and retrieving bioconcept annotations in full text biomedical articles …

Motivation Text mining has become an important tool for biomedical research. The most
fundamental text-mining task is the recognition of biomedical named entities (NER), such as …

Community-run, formal evaluations and manually annotated text corpora are critically
important for advancing biomedical text-mining research. Recently in BioCreative V, a new …

PubMed® is an essential resource for the medical domain, but useful concepts are either
difficult to extract or are ambiguous, which has significantly hindered knowledge discovery …

The emergence of “big data” initiatives has led to the need for tools that can automatically
extract valuable chemical information from large volumes of unstructured data, such as the …