"few-shot" meaning in English

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      "expansion": "few-shot (not comparable)",
      "name": "en-adj"
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  "lang": "English",
  "lang_code": "en",
  "pos": "adj",
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          "langcode": "en",
          "name": "Artificial intelligence",
          "orig": "en:Artificial intelligence",
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      "examples": [
        {
          "ref": "2023 October 30, Herbold et al., “A large-scale comparison of human-written versus ChatGPT-generated essays”, in Scientific Reports, volume 13, page 4",
          "text": "No additional prompts for getting the responses were used, i.e. the data was created with a basic prompt in a zero-shot scenario. This is in contrast to the benchmarks by OpenAI, who used an engineered prompt in a few-shot scenario to guide the generation of essays.",
          "type": "quotation"
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      ],
      "glosses": [
        "A machine learning paradigm where a model is trained on a very small amount of data, typically less than that required for traditional machine learning approaches."
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      "id": "en-few-shot-en-adj-T-8OHTZA",
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      "qualifier": "machine learning",
      "raw_glosses": [
        "(machine learning, attributive) A machine learning paradigm where a model is trained on a very small amount of data, typically less than that required for traditional machine learning approaches."
      ],
      "tags": [
        "attributive",
        "not-comparable"
      ]
    }
  ],
  "word": "few-shot"
}

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      "expansion": "few-shot (not comparable)",
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  "lang_code": "en",
  "pos": "adj",
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          "ref": "2023 October 30, Herbold et al., “A large-scale comparison of human-written versus ChatGPT-generated essays”, in Scientific Reports, volume 13, page 4",
          "text": "No additional prompts for getting the responses were used, i.e. the data was created with a basic prompt in a zero-shot scenario. This is in contrast to the benchmarks by OpenAI, who used an engineered prompt in a few-shot scenario to guide the generation of essays.",
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      ],
      "glosses": [
        "A machine learning paradigm where a model is trained on a very small amount of data, typically less than that required for traditional machine learning approaches."
      ],
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        "(machine learning, attributive) A machine learning paradigm where a model is trained on a very small amount of data, typically less than that required for traditional machine learning approaches."
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        "attributive",
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  "word": "few-shot"
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