Semantic Parsing at Bloomberg

Code generation — and semantic parsing in particular — enables the creation of natural language interfaces for interacting with the vast trove of financial data provided by Bloomberg. This data is available both in structured repositories and through dedicated APIs. In this sponsored talk, we discuss the potential of these technologies to democratize access and empower users to perform complex financial analyses and analytics. We will also highlight two of Bloomberg's recent publications at EMNLP 2025: one on calibrating text-to-SQL outputs from large language models without retraining, and another that introduced STARQA, a dataset for testing complex analytical reasoning and real-world query understanding.