Hello there! I’m Paramita (sounds similar to ‘parameter’) and I’m excited to be part of the Relation Extraction research team at Diffbot.
I received my PhD degree from the University of Trento/FBK-ICT in spring 2016. Under the supervision of Sara Tonelli, my PhD research focused on extracting temporal and causal relations between events from natural language texts, as part of the NewsReader project. I then joined Gerhard Weikum‘s group at Max Planck Institute for Informatics, where YAGO (Yet Another Great Ontology) Knowledge Base was developed, as a Postdoc. My research interests have always been revolved around Information Extraction and Machine Learning approach for it, making sense of unstructured text and building structured knowledge out of it.
I learned more about Diffbot when I attended ISWC’18 in Monterey, and found out that they’re on their steadfastly way on building a gigantic knowledge graph out of the whole web. I got hooked and decided to temporarily escape rainy Germany to sunny California. Here at Diffbot, I’ll be working on extracting temporal qualifiers for facts extracted to build Diffbot Knowledge Graph, making sure that we can differentiate fresh facts from the historical ones. I would love to hear your ideas and suggestions on how to make that happen!