This masterclass explores the exciting world of automatically populating knowledge graphs using Natural Language Processing (NLP). The podcast is organized into sections that delve into entity discovery and relation extraction, along with important methodological insights. The speaker showcases how to use the Sentence-BERT library for relation extraction, demonstrating the process of fine-tuning a pre-trained model with specific domain data to enhance its ability to identify synonymous occupations accurately. A key takeaway is that while NLP tools are incredibly powerful, it's essential to carefully select data, ensure semantic clarity, and acknowledge potential biases to create reliable knowledge graphs. This underlines the importance of human validation and a solid methodology in the process.
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