Add usage examples

README.md

@@ -102,10 +102,24 @@ This distinction is also reflected in the configuration names:
 
 <p id="p-list-base-configs">The configuration names (as replacements for <code>&lt;config&gt;</code>) in this dataset are:</p>
 
-- `main`: 8865 arguments (sources: `A`, `D`, `E`) with splits `train`, `validation`, and `test`
+- `main`: 8865 arguments (sources: `A`, `D`, `E`) with splits `train`, `validation`, and `test` (default configuration name)
+  ```python
+  dataset_main_train = load_dataset("webis/Touche23-ValueEval", split="train")
+  dataset_main_validation = load_dataset("webis/Touche23-ValueEval", split="validation")
+  dataset_main_test = load_dataset("webis/Touche23-ValueEval", split="test")
+  ```
 - `nahjalbalagha`: 279 arguments (source: `F`) with split `test`
+  ```python
+  dataset_nahjalbalagha_test = load_dataset("webis/Touche23-ValueEval", name="nahjalbalagha", split="test")
+  ```
 - `nyt`: 80 arguments (source: `G`) with split `test`
+  ```python
+  dataset_nyt_test = load_dataset("webis/Touche23-ValueEval", name="nyt", split="test")
+  ```
 - `zhihu`: 100 arguments (source: `C`) with split `validation`
+  ```python
+  dataset_zhihu_validation = load_dataset("webis/Touche23-ValueEval", name="zhihu", split="validation")
+  ```
 
 Please note that due to copyright reasons, there currently does not exist a direct download link to the arguments contained in the
 New york Times
@@ -124,17 +138,29 @@ The following lists all configuration names for metadata. Each configuration onl
     - `MACE-P`: the quality label according to the MACE-P scoring function
     - `stance_WA`: the stance label according to the weighted-average scoring function
     - `stance_WA_conf`: the confidence in the stance label according to the weighted-average scoring function
+  ```python
+  dataset_ibm_metadata = load_dataset("webis/Touche23-ValueEval", name="ibm-meta", split="meta")
+  ```
 - `zhihu-meta`: Each row corresponds to one argument (IDs starting with `C`) from the Chinese question-answering website [Zhihu](https://www.zhihu.com)
     - `Argument ID`: The unique identifier for the argument
     - `Conclusion Chinese`: The original chinese conclusion statement
     - `Premise Chinese`: The original chinese premise statement
     - `URL`: Link to the original statement the argument was taken from
+  ```python
+  dataset_zhihu_metadata = load_dataset("webis/Touche23-ValueEval", name="zhihu-meta", split="meta")
+  ```
 - `gdi-meta`: Each row corresponds to one argument (IDs starting with `D`) from [GD IDEAS](https://www.groupdiscussionideas.com/)
     - `Argument ID`: The unique identifier for the argument
     - `URL`: Link to the topic the argument was taken from
+  ```python
+  dataset_gdi_metadata = load_dataset("webis/Touche23-ValueEval", name="gdi-meta", split="meta")
+  ```
 - `cofe-meta`: Each row corresponds to one argument (IDs starting with `E`) from [the Conference for the Future of Europe](https://futureu.europa.eu)
     - `Argument ID`: The unique identifier for the argument
     - `URL`: Link to the comment the argument was taken from
+  ```python
+  dataset_cofe_metadata = load_dataset("webis/Touche23-ValueEval", name="cofe-meta", split="meta")
+  ```
 - `nahjalbalagha-meta`: Each row corresponds to one argument (IDs starting with `F`). This file contains information on the 279 arguments in `nahjalbalagha` (or `nahjalbalagha-level1`)
     and 1047 additional arguments that were not labeled so far. This data was contributed by the language.ml lab.
     - `Argument ID`: The unique identifier for the argument
@@ -146,10 +172,16 @@ The following lists all configuration names for metadata. Each configuration onl
     - `Premise English`: Premise text of the argument in English (translated from Farsi)
     - `Source`: Source text of the argument; one of "Nahj al-Balagha", "Ghurar al-Hikam wa Durar ak-Kalim"; their Farsi translations were used
     - `Method`: How the premise was extracted from the source; one of "extracted" (directly taken), "deduced"; the conclusion are deduced
+  ```python
+  dataset_nahjalbalagha_metadata = load_dataset("webis/Touche23-ValueEval", name="nahjalbalagha-meta", split="meta")
+  ```
 - `nyt-meta`: Each row corresponds to one argument (IDs starting with `G`) from [The New York Times](https://www.nytimes.com)
     - `Argument ID`: The unique identifier for the argument
     - `URL`: Link to the article the argument was taken from
     - `Internet Archive timestamp`: Timestamp of the article's version in the Internet Archive that was used
+  ```python
+  dataset_nyt_metadata = load_dataset("webis/Touche23-ValueEval", name="nyt-meta", split="meta")
+  ```
 - `value-categories`: Contains a single JSON-entry with the structure of level 2 and level 1 values regarding the value taxonomy:
   ```
   {
@@ -161,6 +193,10 @@ The following lists all configuration names for metadata. Each configuration onl
     }, ...
   }
   ```
+  As this configuration contains just a single entry, an example usage could be:
+  ```python
+  value_categories = load_dataset("webis/Touche23-ValueEval", name="value-categories", split="meta")[0]
+  ```
 
 ## Additional Information