AXE: Low-Cost Cross-Domain Web Structured Information Extraction

• URL: http://arxiv.org/abs/2602.01838v1
• Date: Mon, 02 Feb 2026 09:09:35 GMT
• Title: AXE: Low-Cost Cross-Domain Web Structured Information Extraction
• Authors: Abdelrahman Mansour, Khaled W. Alshaer, Moataz Elsaban,
• Abstract summary: AXE is a pipeline that treats the HTML DOM as a tree that needs pruning rather than just a wall of text to be read.<n>AXE uses a specialized "pruning" mechanism to strip away boilerplate and irrelevant nodes.<n>We aim to provide a practical, cost-effective path for large-scale web information extraction.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Extracting structured data from the web is often a trade-off between the brittle nature of manual heuristics and the prohibitive cost of Large Language Models. We introduce AXE (Adaptive X-Path Extractor), a pipeline that rethinks this process by treating the HTML DOM as a tree that needs pruning rather than just a wall of text to be read. AXE uses a specialized "pruning" mechanism to strip away boilerplate and irrelevant nodes, leaving behind a distilled, high-density context that allows a tiny 0.6B LLM to generate precise, structured outputs. To keep the model honest, we implement Grounded XPath Resolution (GXR), ensuring every extraction is physically traceable to a source node. Despite its low footprint, AXE achieves state-of-the-art zero-shot performance, outperforming several much larger, fully-trained alternatives with an F1 score of 88.1% on the SWDE dataset. By releasing our specialized adaptors, we aim to provide a practical, cost-effective path for large-scale web information extraction.

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