Regulatory Query Assistant

Using the Legal Regulation Search Assistant as an example, in the past, government agencies and enterprises were limited by technical constraints and could only use keyword search methods to query data. However, keyword search has the following shortcomings:

1. Poor semantic understanding, inaccurate results

2. Unable to ask multiple questions at once

3. Affected by spelling errors

4. Unable to integrate answers to multiple questions

The above shortcomings lead to poor user experience. However, with the emergence of large language models and RAG, everything has changed. The following is a comparison table between traditional keyword search and RAG search:

	Traditional Keyword Search	RAG Search
Query Understanding	Limited to exact matching and basic synonyms	Understands context, intent, and nuanced meanings
Information Retrieval	Based on keyword frequency and basic relevance algorithms	Uses semantic similarity and context-aware retrieval
Result Format	List of potentially relevant documents	List of potentially relevant documents Synthesized answers citing source documents
Handling Complex Queries	Usually requires multiple searches and manual integration	Can directly handle complex multi-faceted questions
Ability to Adapt to Domain-Specific Terminology	Limited unless heavily customized	Can learn and adapt to organization-specific terminology
Ability to Use Unstructured Data	Very limited	High, can extract insights from various document types
Continuous Learning	Typically static unless manually updated	Can improve over time through usage and feedback

Taking the "Government Legal Regulation Search Assistant" as an example, as shown in the legal regulation announcements from the Ministry of the Interior's National Land Management Agency below, keyword search was used in the past. Now, we hope to improve user convenience through generative AI technology. This can be done on MaiAgent.

https://www.nlma.gov.tw/最新消息/法規公告.html

Creating a "Legal Regulation Search Assistant" on the MaiAgent Platform

The structure for creating a "Legal Regulation Search Assistant" is as follows:

Because generative AI may pose risks for government agencies, in terms of design, we hope to have different response methods for internal staff and public users:

Usage entry points and architecture:

For the question Are there age restrictions for funding subsidies?, the desired responses for internal staff and the general public are as follows:

Response received by internal staff:

Response received by the general public:

We only need to provide different Role Instructions when creating the "AI Assistant" in MaiAgent to achieve this effect. The following provides AI assistant role instructions for both General Public and Internal Staff.

Role Instructions (General Public Version)

# Role
You are a legal regulation search assistant for the Ministry of the Interior's National Land Management Agency

# Output Format
Please use the format in the example below to respond with the three most relevant regulations.

<example>
The issues you mentioned are related to the following regulations:

1. <Date> <Category> <Regulation Type> [Title](URL)
2. <Date> <Category> <Regulation Type> [Title](URL)
3. <Date> <Category> <Regulation Type> [Title](URL)
</example>

# Output Restrictions
- Please respond in Traditional Chinese
- Prioritize data with more recent dates as reference material
- Do not answer information outside the scope of the knowledge base
- Answer based on knowledge base data; if unable to answer, respond with the text in the <example> below

<example>
We apologize, but the current knowledge base does not contain the regulation information you are inquiring about. Please contact us during our office hours.

Office Hours: Monday to Friday, 8:00~17:30
Contact numbers for various business units: Please refer to [link](<https://www.nlma.gov.tw/%E6%9C%AC%E7%BD%B2%E6%9C%8D%E5%8B%99%E8%B3%87%E8%A8%8A.html>)
</example>

Role Instructions (Internal Staff Version)

# Role
You are a legal regulation search assistant for the Ministry of the Interior's National Land Management Agency

# Background
This year is 2024 CE, Republic of China year 113

# Output Format
Please use the format in the example below to respond with the three most relevant regulations.

<example>
{Response based on the question and reference materials}

Related Regulations:
1. <Date> <Category> <Regulation Type> [Title](URL)
2. <Date> <Category> <Regulation Type> [Title](URL)
3. <Date> <Category> <Regulation Type> [Title](URL)
</example>

# Output Restrictions
- Please respond in Traditional Chinese
- Prioritize data with more recent dates as reference material
- Do not answer information outside the scope of the knowledge base
- Answer based on knowledge base data; if unable to answer, respond with the text in the <example> below

<example>
The current knowledge base does not contain the regulation information you are inquiring about. Please supplement with regulation data.
</example>

Knowledge Base

Download past regulation documents from Ministry of the Interior National Land Management Agency Legal Regulation Search

Legal Regulation Search.xlsx

National Spatial Planning Land Violation Reporting Reward Measures	National Spatial Planning Division	Regulatory Order	2024-10-31	Regulation Content…	https://www.nlma.gov.tw//政府資訊公開/主動公開資訊/中央法規/法規查詢/25-計畫組/39226-國土計畫土地違規使用檢舉獎勵辦法.html
Public Place Parent-Child Toilet and Washroom Installation Measures	Building Management Division	Regulatory Order	2024-10-30	Regulation Content…	https://www.nlma.gov.tw//政府資訊公開/主動公開資訊/中央法規/法規查詢/30-建管組/28714-公共場所親子廁所盥洗室設置辦法.html
Notice of Amendment to "Ministry of the Interior Social Housing Rental Measures"	Housing Development Division	Draft Regulation	2024-10-22	Regulation Content…	https://www.nlma.gov.tw//政府資訊公開/主動公開資訊/中央法規/法規查詢/29-住宅組/39204-預告修正「內政部興辦社會住宅出租辦法」。.html