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msra-nlc/MSParS

0
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183 stars·37 forks·9 views

MSParS

MSParS is a large-scale dataset for the open domain semantic parsing task. The whole dataset consists of 81,826 samples annotated by native English speakers. We randomly shuffle these samples and use 80% of them (63,826) as training set, 10% as validation set (9,000), and the remaining 10% as…

Features

  • Research and Datasets - Dataset for machine reading comprehension and text processing.

Star history

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How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with MSParS

These projects share indexed features with MSParS. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • abhshkdz/ai-deadlinesabhshkdz avatar

    abhshkdz/ai-deadlines

    5,989View on GitHub↗

    ai-deadlines is a tracker for submission dates across machine learning, computer vision, and natural language processing research conferences. It functions as a specialized calendar and monitor to help researchers track important conference date milestones. The project provides chronological timelines and countdown timers for top-tier artificial intelligence venues. This covers the publication cycle for academic papers in the ML, CV, and NLP domains.

    JavaScript
    View on GitHub↗5,989
  • embedding/chinese-word-vectorsEmbedding avatar

    Embedding/Chinese-Word-Vectors

    12,227View on GitHub↗

    This project is a collection of pre-trained dense and sparse word vectors trained on diverse Chinese corpora. It serves as a library of linguistic representations and an NLP vector dataset designed to improve the accuracy of semantic and morphological analysis in text models. The collection provides corpus-specific representations and utilizes n-gram co-occurrence modeling to capture diverse linguistic patterns. It includes a hybrid of dense-sparse vectors to balance computational efficiency and semantic precision. The project covers semantic vector search and the development of Chinese natu

    Pythonchinesechinese-word-segmentationembedding
    View on GitHub↗12,227
  • sfikas/medical-imaging-datasetssfikas avatar

    sfikas/medical-imaging-datasets

    2,558View on GitHub↗

    A list of Medical imaging datasets.

    image-datasetmedical-imaging
    View on GitHub↗2,558

Frequently asked questions

What does msra-nlc/mspars do?

MSParS is a large-scale dataset for the open domain semantic parsing task. The whole dataset consists of 81,826 samples annotated by native English speakers. We randomly shuffle these samples and use 80\% of them (63,826) as training set, 10\% as validation set (9,000), and the remaining 10\% as…

What are the main features of msra-nlc/mspars?

The main features of msra-nlc/mspars are: Research and Datasets.

Which projects share features with msra-nlc/mspars?

Projects with overlapping indexed features include: abhshkdz/ai-deadlines — ai-deadlines is a tracker for submission dates across machine learning, computer vision, and natural language… embedding/chinese-word-vectors — This project is a collection of pre-trained dense and sparse word vectors trained on diverse Chinese corpora. It… sfikas/medical-imaging-datasets — A list of Medical imaging datasets.