Elsevier, Inc.

Subhradeep Kayal

Michelle Gregory

Georgios Tsatsaronis

Zubair Afzal

Systems and methods of extracting funding information from text are disclosed herein. The method includes receiving a text document, extracting paragraphs from the text document using a natural language processing model or a machine learning model, and classifying, using a machine learning classifier, the paragraphs as having funding information or not having funding information. The method further includes labeling, using a first annotator, potential entities within the paragraphs classified as having funding information, and labeling, using a second annotator, potential entities within the paragraphs classified as having funding information, where the first annotator implements a first named-entity recognition model and the second annotator implements a second named-entity recognition model that is different from the first named-entity recognition model. The method further includes extracting the potential entities from the paragraphs classified as having funding information and determining, using an ensemble mechanism, funding information from the potential entities.

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Amsterdam, Netherlands

Subhradeep Kayal