Row 4019

Row ID: 4019 | Dataset Entry | Axioma AXP Content Repository

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It's pretty easy to ask LLM to check/paraphrase/proofread an input. But for example if we want to build something similar to grammarly where LLM can help identify exact problems in the input, how can you do so?

Example:

Input: proof read the following sentence: "This snetence have a typo in the sentence."

Output: (just an example we encode the position split by whitespaces) { 2: { suggestion: "sentence", reason: "typo" }, 3: { suggestion: "has", reason: "grammar", }, }

Or another similar use case is to output the range of semantically close subsection of the input for chunking purpose. To save on output token, we don't really want the LLM to output the entire list of subsections, just the start and end position.

So yeah, is there any solution to these using LLM? Or one would have to finetune a specialized model for that?

FieldValue
text It's pretty easy to ask LLM to check/paraphrase/proofread an input. But for example if we want to build something similar to grammarly where LLM can help identify exact problems in the input, how can you do so? Example: Input: proof read the following sentence: "This snetence have a typo in the sentence." Output: (just an example we encode the position split by whitespaces) { 2: { suggestion: "sentence", reason: "typo" }, 3: { suggestion: "has", reason: "grammar", }, } Or an…
label r/gpt3
dataType post
communityName r/GPT3
datetime 2024-04-01
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Raw Record

{
  "text": "It's pretty easy to ask LLM to check/paraphrase/proofread an input. But for example if we want to build something similar to grammarly where LLM can help identify exact problems in the input, how can you do so?\n\nExample:\n\n    Input: proof read the following sentence: \"This snetence have a typo in the sentence.\" \n\n    Output: (just an example we encode the position split by whitespaces) \n{ \n  2: { suggestion: \"sentence\", reason: \"typo\" }, \n  3: { suggestion: \"has\", reason: \"grammar\", }, \n}\n\nOr another similar use case is to output the range of semantically close subsection of the input for chunking purpose. To save on output token, we don't really want the LLM to output the entire list of subsections, just the start and end position.\n\nSo yeah, is there any solution to these using LLM? Or one would have to finetune a specialized model for that?",
  "label": "r/gpt3",
  "dataType": "post",
  "communityName": "r/GPT3",
  "datetime": "2024-04-01",
  "username_encoded": "Z0FBQUFBQm5Lakwxd2J5UUUxYTNKYmsxZjdiQkMxQkdFc3lPRXFRV2VFMXpLMHlhNVMwTUxiNlZSZHl4eFZlVjA3dUE0elUxMWw4R1RzRHliejE0ZXVBd3ZnZjhkbUIxU0RZSXdRZno1WDFINzNzcFlVZlRNR2c9",
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}
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