This study aimed to develop a fully automated approach for extracting ranking information from online search platforms. The researchers created a template that guides the algorithm to generate answers based solely on the provided paragraphs, with citations for transparency. They confined their search to the primary web pages of six platforms and excluded audiovisual content. The study found that fully automated tools cannot replace legal experts but can be effective in continuously tracking changes in documentation. To address this challenge, the researchers devised an improved strategy that incorporates advanced prompt engineering and more transparent answer retrieval mechanisms.
The study focused on textual content, as required by law, and found that the number of associated links and average word count per document varied across platforms. The online repository provides further details. While some platforms feature video content or imagery, the study prioritized textual content to ensure compliance with legal requirements.
The researchers used prompt engineering to formulate precise task descriptions and examples to steer the responses of language models. They found that fully automated tools cannot entirely replace legal experts but can be useful in tandem with them. The improved strategy incorporates advanced prompt engineering and more transparent answer retrieval mechanisms to effectively summarize lengthy documentation.
In simple terms, the study aimed to create a way for computers to automatically extract information about how search engines rank web pages. The researchers developed a template that tells the computer to only use the text provided, and if possible, to find answers based on what is written in the paragraphs. They also made sure to include citations so that the answers can be trusted. The study found that while computers can help with this task, they are not yet good enough to completely replace lawyers who understand the law. To solve this problem, the researchers came up with a new way of teaching computers how to do this job better.
Key points
- The study aimed to create a fully automated approach for extracting ranking information from online search platforms.
- The researchers developed a template that guides the algorithm to generate answers based solely on the provided paragraphs, with citations for transparency.
- The study found that fully automated tools cannot replace legal experts but can be effective in continuously tracking changes in documentation.
- The researchers devised an improved strategy that incorporates advanced prompt engineering and more transparent answer retrieval mechanisms to effectively summarize lengthy documentation.
- The study focused on textual content, as required by law, and found variations in the number of associated links and average word count per document across platforms.
- The online repository provides further details.
- While some platforms feature video content or imagery, the study prioritized textual content to ensure compliance with legal requirements.
- Prompt engineering was used to formulate precise task descriptions and examples to steer the responses of language models.
