Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …

Automatic knowledge graph construction aims at manufacturing structured human
knowledge. To this end, much effort has historically been spent extracting informative fact …

Deep learning has yielded state-of-the-art performance on many natural language
processing tasks including named entity recognition (NER). However, this typically requires …

Selection of text feature item is a basic and important matter for text mining and information
retrieval. Traditional methods of feature extraction require handcrafted features. To hand …

This article reviews recent advances in applying natural language processing (NLP) to
Electronic Health Records (EHRs) for computational phenotyping. NLP-based …

Event trigger detection, entity mention recognition, event argument extraction, and relation
extraction are the four important tasks in information extraction that have been performed …

The rapid development of data and artificial intelligence technology has introduced new
opportunities and challenges to aeronautical information intelligence. However, there are …

Recognizing software entities such as library names from free-form text is essential to
enable many software engineering (SE) technologies, such as traceability link recovery …

Event factuality prediction (EFP) is the task of assessing the degree to which an event
mentioned in a sentence has happened. For this task, both syntactic and semantic …

This is the first time New York University (NYU) participates in the event nugget (EN)
evaluation of the Text Analysis Conference (TAC). We developed EN systems for both …