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  This dataset is provided by the research "Concreteness ratings for 40 thousand generally known English word lemmas" of Brysbaert et al. (2014).
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  The original dataset can be found [here](https://osf.io/kj76e/).
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- ## Column Description
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- | **Column Name** | **Description** | **Values** |
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- |------------------------------|-----------------------------------------------------------|--------------------------------------------------------------------------------------------------|
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- | `WorkerId` | Unique Amazon Mechanical Turk personal ID | |
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- | `WorkTimeInSeconds` | Time between accepting and submitting the assignment | |
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- | `LifetimeApprovalRate` | Prior assignments approved | |
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- | `Last30DaysApprovalRate` | Prior assignments approved in the last 30 days | |
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- | `Last7DaysApprovalRate` | Prior assignments approved in the last 7 days | |
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- | `Answer.QAge` | Responder's age | |
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- | `Answer.QEducation` | Level of education that describes the responder best | Some high school; high school graduate; some college-no degree; Associates degree; Bachelors degree; Masters degree; Doctorate; Unspecified |
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- | `Answer.QGender` | Responder's gender | Female; Male; Unspecified |
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- | `Answer.QHand` | Responder's dominant hand | Left; Right; Unspecified |
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- | `Answer.QLang` | Responder's language(s) | |
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- | `Answer.QRaised` | State where the responder lived most of the time before age 7 | US states |
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- | `Word` | Stimulus word | |
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- | `Rating` | Rating of the stimulus word | 1-5 or "n"/"N" for unknown word |
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-
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  ## Usage
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  This dataset is ideal for training and evaluating machine learning models for English word concreteness.
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  This dataset is provided by the research "Concreteness ratings for 40 thousand generally known English word lemmas" of Brysbaert et al. (2014).
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  The original dataset can be found [here](https://osf.io/kj76e/).
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  ## Usage
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  This dataset is ideal for training and evaluating machine learning models for English word concreteness.
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