This article describes how a hybrid architecture that combines third‑party address‑recognition APIs with large‑language‑model (LLM) processing, along with carefully engineered prompts and a TSV output format, dramatically improves address parsing accuracy and latency in a retail checkout scenario.
This article demonstrates how to build an automatic address recognition feature for user input by combining Laravel backend controllers, repository services, and jQuery AJAX calls to parse, validate, and populate name, mobile, and detailed address fields.
This article introduces the cpca Python module that parses free‑form Chinese address strings into province, city, and district fields, explains how to install it, demonstrates basic and advanced usage with code examples, and describes optional full‑text and map‑drawing features.
This article introduces GeoBERT, a novel pre‑training method for Chinese address strings that leverages seven jointly constrained tasks to capture spatial semantics, administrative hierarchy, and similarity relationships, enabling downstream address classification, segmentation, POI extraction, similarity comparison, and authenticity verification with reduced annotation dependence.
