| # PIE Dataset Card for "argmicro" | |
| This is a [PyTorch-IE](https://github.com/ChristophAlt/pytorch-ie) wrapper for the | |
| [ArgMicro Huggingface dataset loading script](https://huggingface.co/datasets/DFKI-SLT/argmicro). | |
| ## Dataset Variants | |
| The dataset contains two `BuilderConfig`'s: | |
| - `de`: with the original texts collection in German | |
| - `en`: with the English-translated texts | |
| ## Data Schema | |
| The document type for this dataset is `ArgMicroDocument` which defines the following data fields: | |
| - `text` (str) | |
| - `id` (str, optional) | |
| - `topic_id` (str, optional) | |
| - `metadata` (dictionary, optional) | |
| and the following annotation layers: | |
| - `stance` (annotation type: `Label`) | |
| - description: A document may contain one of these `stance` labels: `pro`, `con`, `unclear`, or no label when it is undefined (see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L35) for reference). | |
| - `edus` (annotation type: `Span`, target: `text`) | |
| - `adus` (annotation type: `LabeledAnnotationCollection`, target: `edus`) | |
| - description: each element of `adus` may consist of several entries from `edus`, so we require `LabeledAnnotationCollection` as annotation type. This is originally indicated by `seg` edges in the data. | |
| - `LabeledAnnotationCollection` has the following fields: | |
| - `annotations` (annotation type: `Span`, target: `text`) | |
| - `label` (str, optional), values: `opp`, `pro` (see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L36)) | |
| - `relations` (annotation type: `MultiRelation`, target: `adus`) | |
| - description: Undercut (`und`) relations originally target other relations (i.e. edges), but we let them target the `head` of the targeted relation instead. The original state can be deterministically reconstructed by taking the label into account. Furthermore, the head of additional source (`add`) relations are integrated into the head of the target relation (note that this propagates along `und` relations). We model this with `MultiRelation`s whose `head` and `tail` are of type `LabeledAnnotationCollection`. | |
| - `MultiRelation` has the following fields: | |
| - `head` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) | |
| - `tail` (tuple, annotation type: `LabeledAnnotationCollection`, target: `adus`) | |
| - `label` (str, optional), values: `sup`, `exa`, `reb`, `und` (see [here](https://huggingface.co/datasets/DFKI-SLT/argmicro/blob/main/argmicro.py#L37) for reference, but note that helper relations `seg` and `add` are not there anymore, see above). | |
| See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/annotations.py) for the annotation type definitions. | |
| ## Document Converters | |
| The dataset provides document converters for the following target document types: | |
| - `pytorch_ie.documents.TextDocumentWithLabeledSpansAndBinaryRelations` | |
| - `LabeledSpans`, converted from `ArgMicroDocument`'s `adus` | |
| - labels: `opp`, `pro` | |
| - if an ADU contains multiple spans (i.e. EDUs), we take the start of the first EDU and the end of the last EDU as the boundaries of the new `LabeledSpan`. We also raise exceptions if any newly created `LabeledSpan`s overlap. | |
| - `BinraryRelations`, converted from `ArgMicroDocument`'s `relations` | |
| - labels: `sup`, `reb`, `und`, `joint`, `exa` | |
| - if the `head` or `tail` consists of multiple `adus`, then we build `BinaryRelation`s with all `head`-`tail` combinations and take the label from the original relation. Then, we build `BinaryRelations`' with label `joint` between each component that previously belongs to the same `head` or `tail`, respectively. | |
| - `metadata`, we keep the `ArgMicroDocument`'s `metadata`, but `stance` and `topic_id`. | |
| See [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/documents.py) for the document type | |
| definitions. | |