Understanding how computers interpret and represent human language is a key challenge in natural language processing. By working with AMR and RDF, this project introduces students to two important frameworks for semantic representation. Using the py_amr2fred library, the project demonstrates how website text can be systematically converted into JSON-LD, offering a practical example of bridging unstructured text with structured semantic data. The resulting application not only highlights the conversion pipeline but also provides valuable insights into the role of semantic technologies in knowledge representation.
Technologies: Web Applications; Web Services; Python; amr2fred; rdflib
Tags: FactCheck; Python; Web Application; Web Service; ARM; Hofer; RDFLib