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@@ -92,13 +92,43 @@ The text in the dataset is in English and German, as written by researchers. The
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  The following data fields are provided for documents:
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  `sentence`: Textual instance, which may contain a variable mention.<br />
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  `is_variable`: Label, whether the textual instance contains a variable mention (1) or not (0). This column can be used for Task 1 (Variable Detection).<br />
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- `variable`: Variables (separated by a comma ";") that are mentioned in the textual instance. This column can be used for Task 2 (Variable Disambiguation).<br />
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  `research_data`: Research data IDs (separated by a ";") that are relevant for each instance (and in general for each "doc_id").<br />
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  `doc_id`: ID of the source document. Each document is written in one language (either English or German).<br />
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  `uuid`: Unique ID of the instance in uuid4 format.<br />
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  `lang`: Language of the sentence.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Data Splits
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  The following data fields are provided for documents:
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+ ```
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  `sentence`: Textual instance, which may contain a variable mention.<br />
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  `is_variable`: Label, whether the textual instance contains a variable mention (1) or not (0). This column can be used for Task 1 (Variable Detection).<br />
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+ `variable`: Variables (separated by a comma ";") that are mentioned in the textual instance. This column can be used for Task 2 (Variable Disambiguation). Variables with the "unk" tag could not be mapped to a unique variable.<br />
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  `research_data`: Research data IDs (separated by a ";") that are relevant for each instance (and in general for each "doc_id").<br />
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  `doc_id`: ID of the source document. Each document is written in one language (either English or German).<br />
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  `uuid`: Unique ID of the instance in uuid4 format.<br />
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  `lang`: Language of the sentence.
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+ ```
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+
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+ The language for each document can be found in the document-language mapping file [here](https://github.com/vadis-project/sv-ident/blob/main/data/train/document_languages.json), which maps `doc_id` to a language code (`en`, `de`). The variables metadata (i.e., the vocabulary) can be downloaded from this [link](https://drive.google.com/file/d/18slgACOcE8-_xIDX09GrdpFSqRRcBiON/view?usp=sharing). Note, that each `research_data` contains hundreds of variables (these can be understood as the corpus of documents to choose the most relevant from). If the variable has an "unk" tag, it means that the sentence contains a variable that has not been disambiguated. Such sentences could be used for Task 1 and filtered out for Task 2. The metadata file has the following format:
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+
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+ ```
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+ {
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+ "research_data_id_1": {
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+ "variable_id_1": VARIABLE_METADATA,
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+ ...
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+ "variable_id_n": VARIABLE_METADATA,
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+ },
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+ ...
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+ "research_data_id_n": {...},
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+ }
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+ ```
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+
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+ Each variable may contain all (or some) of the following values:
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+ ```
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+ study_title: The title of the research data study.
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+ variable_label: The label of the variable.
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+ variable_name: The name of the variable.
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+ question_text: The question of the variable in the original language.
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+ question_text_en: The question of the variable in English.
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+ sub_question: The sub-question of the variable.
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+ item_categories: The item categories of the variable.
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+ answer_categories: The answers of the variable.
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+ topic: The topics of the variable in the original language.
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+ topic_en: The topics of the variable in English.
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+ ```
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  ### Data Splits
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