Researchers have developed an end-to-end pipeline to extract structured data from heterogeneous real estate documents, including scanned forms and complex layouts. The system classifies documents into three categories and then uses the DeepSeek R1 large language model to extract 35 predefined property attributes, returning the data as a JSON object. This method successfully processed 2781 documents, yielding 2766 unique property records with validated data quality, demonstrating feasibility and reliability for large-scale extraction. AI
IMPACT This research demonstrates a viable method for extracting structured data from complex, unstructured documents using LLMs, potentially improving data accessibility in fields like real estate.
RANK_REASON The cluster describes a research paper detailing a new method for data extraction.
- arXiv
- Carlos Francisco Moreno-García
- DeepSeek R1
- Hugging Face
- JSON
- k-means clustering
- REST APIs
- alphaXiv
- CatalyzeX
- DagsHub
- Gotit.pub
- ScienceCast
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