Extraction Prompt & Response Dataset in Dutch
This extraction prompt and completion dataset consists of a wide range of extraction prompts and responses in the Dutch language. Along with that, it includes detailed annotation for each dataset.
Extraction Prompt-Completion Dataset
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About This OTS Dataset
Welcome to the Dutch Extraction Type Prompt-Response Dataset, a meticulously curated collection of 1500 prompt and response pairs. This dataset is a valuable resource for enhancing the data extraction abilities of Language Models (LMs), a critical aspect in advancing generative AI.
This extraction dataset comprises a diverse set of prompts and responses where the prompt contains input text, extraction instruction, constraints, and restrictions while completion contains the most accurate extraction data for the given prompt. Both these prompts and completions are available in Dutch language.
These prompt and completion pairs cover a broad range of topics, including science, history, technology, geography, literature, current affairs, and more. Each prompt is accompanied by a response, providing valuable information and insights to enhance the language model training process. Both the prompt and response were manually curated by native Dutch people, and references were taken from diverse sources like books, news articles, websites, and other reliable references.
This dataset encompasses various prompt types, including instruction type, continuation type, and in-context learning (zero-shot, few-shot) type. Additionally, you'll find prompts and responses containing rich text elements, such as tables, code, JSON, etc., all in proper markdown format.
To ensure diversity, this extraction dataset includes prompts with varying complexity levels, ranging from easy to medium and hard. Additionally, prompts are diverse in terms of length from short to medium and long, creating a comprehensive variety. The extraction dataset also contains prompts with constraints and persona restrictions, which makes it even more useful for LLM training.
To accommodate diverse learning experiences, our dataset incorporates different types of responses depending on the prompt. These formats include single-word, short phrase, single sentence, and paragraph type of response. These responses encompass text strings, numerical values, and date and time, enhancing the language model's ability to generate reliable, coherent, and contextually appropriate answers.
Data Format and Annotation Details:
This fully labeled Dutch Extraction Prompt Completion Dataset is available in JSON and CSV formats. It includes annotation details such as a unique ID, prompt, prompt type, prompt length, prompt complexity, domain, response, response type, and rich text presence.
Quality and Accuracy:
Our dataset upholds the highest standards of quality and accuracy. Each prompt undergoes meticulous validation, and the corresponding responses are thoroughly verified. We prioritize inclusivity, ensuring that the dataset incorporates prompts and completions representing diverse perspectives and writing styles, maintaining an unbiased and discrimination-free stance.
The Dutch version is grammatically accurate without any spelling or grammatical errors. No copyrighted, toxic, or harmful content is used during the construction of this dataset.
Continuous Updates and Customization:
The entire dataset was prepared with the assistance of human curators from the FutureBeeAI crowd community. Ongoing efforts are made to add more assets to this dataset, ensuring its growth and relevance. Additionally, FutureBeeAI offers the ability to gather custom extraction prompt and completion data tailored to specific needs, providing flexibility and customization options.
The dataset, created by FutureBeeAI, is now available for commercial use. Researchers, data scientists, and developers can leverage this fully labeled and ready-to-deploy Dutch Extraction Prompt-Completion Dataset to enhance the data extraction abilities and accurate response generation capabilities of their generative AI models and explore new approaches to NLP tasks.
Language Model Training
Natural Language Understanding
Extraction Prompt & Response Dataset
science, history, technology,...more
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