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README.md
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4. Habituality: Events can also be repetitive (e.g., I went to school there for years; habitual) or not (I stopped by; episodic). I have combined this feature with boundedness given their close relation.
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The most anecdotal content is theorized to involve specific entities with bounded, non-habitual events. But different mixtures of the dimensions can provide gradations of anecdotal focus.
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## AI-based Automatic Identification of Anecdotal Statements in Natural Text
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This repository contains a coding-free tool for deriving labels for the above features from any text.
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It uses the transformer neural networks developed in the dissertation discussed above. Note that this tool is best used for analysis.
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[This other tool](https://huggingface.co/spaces/BabakScrapes/Anecedotal_Discourse_Classifier_Demo) would be more appropriate for demonstration purposes.
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4. Habituality: Events can also be repetitive (e.g., I went to school there for years; habitual) or not (I stopped by; episodic). I have combined this feature with boundedness given their close relation.
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The most anecdotal content is theorized to involve specific entities with bounded, non-habitual events. But different mixtures of the dimensions can provide gradations of anecdotal focus.
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## AI-based Automatic Identification of Anecdotal Statements in Natural Text
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20 |
+
This repository contains a coding-free tool for deriving labels for the above features from any text.
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21 |
It uses the transformer neural networks developed in the dissertation discussed above. Note that this tool is best used for analysis.
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+
[This other tool](https://huggingface.co/spaces/BabakScrapes/Anecedotal_Discourse_Classifier_Demo) would be more appropriate for demonstration purposes. Links and scripts for the corpus it was trained on can be found in [this repository](https://github.com/sfeucht/annotation_evaluation).
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