Sentence examples for recognition of entities from inspiring English sources

An additional optional task, Task 2, involves the recognition of entities and the assignment of these entities.

Feedback from biocurators indicated that the tool needs better recognition of entities and qualities from the free text to improve the recall of the system (currently 'to decrease the low recall of the system') PubTator is a web-based tool that allows biocurators to create, save and export annotations, with similar look and feel as PubMed.

Over the last decade, significant advances in biomedical TM have resulted in a shift in research focus from the recognition of entities to the extraction of more complex information from biomedical literature, e.g., interactions between proteins [ 2] and more detailed relationships between drugs, genes and cells [ 21, 22].

These work demonstrate that the recognition of spatial entities depends on entities' spatial relationships in an image.

The CHEMDNER task of BioCreative IV showed that the automatic recognition of chemical entities from PubMed abstracts is a feasible task by automated named entity recognition systems.

CHEMDNER focuses on the recognition of chemical entities (compounds and drugs names) in text.

Recognition of Named Entities Based on Relations and Detailed Text Analysis.

The taggers will be discussed further below: OSCAR [11] is used for the recognition of chemical entities in text.

One of the most important challenges in chemical text mining is the recognition of chemical entities mentioned in the texts.

The system consists of three steps, i.e., (1) normalization of tweets by detecting and correcting spelling errors; (2) capitalization classifier; and (3) recognition of named entities.

The recognition of chemical entities has to cope with a considerable degree of naming variability encountered between and within different chemical sub-disciplines.