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curl --location 'https://gateway.<baseUrl>/chat//graphql' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer <yourToken>' \
--data '{"query":"mutation CompanyUpdateData($input: CompanyUpdateInput!) {\n  companyUpdateData(input: $input) {\n    id\n    acronyms\n  }\n}","variables":{"input":{"acronyms":[{"acronym":"ARB","text":"Allgemeine Rechtschutzbedingungen (ARB)"}]}}}'

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A similar GraphQL query in postman looks as shown in the below screenshot.

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Behind the scenes?

When a user submits a message in Chat,

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This message is finally used as the user message to pass along the rest of the LLM data pipeline.

Important

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Tips

1. Case Sensitivity:

   • Acronyms are case-sensitive. This is

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1. • crucial to prevent them from being mistaken for common

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1. • words or phrases. For example, "PAS" might have a specific meaning in French

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1. • , and case sensitivity helps to distinguish it correctly.

2. Inclusion of Acronym in Expansion:

   • When expanding an acronym, always include the acronym itself in the expansion in brackets. This practice ensures that both the acronym and its

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1. • expanded form are searchable and comprehensible for the Language Learning Model (LLM). For example,

     • {"acronym": "PAS", "text": "Personnel Allocation System (PAS)"}

2. Per Company Settings:

   • The settings for acronyms are made at company level. This means that each company can itself determine how acronyms are handled to ensure that the company terminology is understood by the system.

3. Avoiding Misinterpretation:

   • Consider that acronyms may have different meanings in different contexts. To avoid confusion, clearly define acronyms within your documentation. This practice helps ensure that acronyms are not misinterpreted or replaced incorrectly.

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