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Chapter and Conference Paper
Cold Is a Disease and D-cold Is a Drug: Identifying Biological Types of Entities in the Biomedical Domain
Automatically extracting different types of knowledge from authoritative biomedical texts, e.g., scientific medical literature, electronic health records etc., and representing it in a computer analyzable as well...
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Chapter and Conference Paper
Virus Causes Flu: Identifying Causality in the Biomedical Domain Using an Ensemble Approach with Target-Specific Semantic Embeddings
Identification of Cause-Effect (CE) relation is crucial for creating a scientific knowledge-base and facilitate question-answering in the biomedical domain. An example sentence having CE relation in the biomed...
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Chapter and Conference Paper
Semantic Templates for Generating Long-Form Technical Questions
Question generation (QG) from technical text has multiple important applications such as creation of question-banks for examinations, interviews as well as in intelligent tutoring systems. However, much of th...
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Chapter and Conference Paper
A Simple Neural Approach to Spatial Role Labelling
Spatial Role Labelling involves identification of text segments which emit spatial semantics such as describing an object of interest, a reference point or the object’s relative position with the reference. Ta...
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Chapter and Conference Paper
An Unsupervised Approach for Cause-Effect Relation Extraction from Biomedical Text
Identification of Cause-effect (CE) relation mentions, along with the arguments, are crucial for creating a scientific knowledge-base. Linguistically complex constructs are used to express CE relations in text...