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Leveraging Domain Knowledge for Inclusive and Bias-aware Humanitarian Response Entry Classification
Accurate and rapid situation analysis during humanitarian crises is critical to delivering humanitarian aid efficiently and is fundamental to humanitarian imperatives and the Leave No One Behind (LNOB) principle.
HumSet: Dataset of Multilingual Information Extraction and Classification for Humanitarian Crisis Response
Timely and effective response to humanitarian crises requires quick and accurate analysis of large amounts of text data - a process that can highly benefit from expert-assisted NLP systems trained on validated and annotated data in the humanitarian response domain.
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