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--- |
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license: cc-by-4.0 |
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task_categories: |
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- text-classification |
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- zero-shot-classification |
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task_ids: |
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- multi-label-classification |
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language: |
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- en |
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tags: |
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- Human Values |
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- Value Detection |
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- Multi-Label |
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pretty_name: Human Value Detection Dataset |
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size_categories: |
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- 1K<n<10K |
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--- |
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# The Touché23-ValueEval Dataset |
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## Table of Contents |
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Dataset Usage](#dataset-usage) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Argument Instances](#argument-instances) |
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- [Metadata Instances](#metadata-instances) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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## Dataset Description |
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- **Homepage:** [https://webis.de/data/touche23-valueeval.html](https://webis.de/data/touche23-valueeval.html) |
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- **Repository:** [Zenodo](https://doi.org/10.5281/zenodo.6814563) |
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- **Paper:** [The Touché23-ValueEval Dataset for Identifying Human Values behind Arguments.](https://webis.de/downloads/publications/papers/mirzakhmedova_2023a.pdf) |
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- **Leaderboard:** [https://touche.webis.de/](https://touche.webis.de/semeval23/touche23-web/index.html#results) |
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- **Point of Contact:** [Webis Group](https://webis.de/people.html) |
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### Dataset Summary |
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The Touché23-ValueEval Dataset comprises 9324 arguments from six different sources. An arguments source is indicated with the first letter of its `Argument ID`: |
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- `A`: [IBM-ArgQ-Rank-30kArgs](https://research.ibm.com/haifa/dept/vst/debating_data.shtml#Argument%20Quality) |
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- `C`:Chinese question-answering website [Zhihu](https://www.zhihu.com) |
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- `D`:[Group Discussion Ideas (GD IDEAS)](https://www.groupdiscussionideas.com) |
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- `E`:[The Conference for the Future of Europe](https://futureu.europa.eu) |
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- `F`:Contribution by the language.ml lab (Doratossadat, Omid, Mohammad, Ehsaneddin) [1]: |
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arguments from the "Nahj al-Balagha" [2] and "Ghurar al-Hikam wa Durar ak-Kalim" [3] |
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- `G`:[The New York Times](https://www.nytimes.com) |
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The annotated labels are based on the value taxonomy published in |
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[Identifying the Human Values behind Arguments](https://webis.de/publications.html#kiesel_2022b) (Kiesel et al. 2022) at ACL'22. |
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[1] https://language.ml |
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[2] https://en.wikipedia.org/wiki/Nahj_al-Balagha |
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[3] https://en.wikipedia.org/wiki/Ghurar_al-Hikam_wa_Durar_al-Kalim |
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### Dataset Usage |
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The default configuration name is `main`. |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("webis/Touche23-ValueEval") |
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print(dataset['train'].info.description) |
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for argument in iter(dataset['train']): |
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print(f"{argument['Argument ID']}: {argument['Stance']} '{argument['Conclusion']}': {argument['Premise']}") |
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``` |
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### Supported Tasks and Leaderboards |
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Human Value Detection |
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### Languages |
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The [Argument Instances](#argument-instances) are all monolingual; it only includes English (mostly en-US) documents. |
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The [Metadata Instances](#metadata-instances) for some dataset parts additionally state the arguments in their original language and phrasing. |
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## Dataset Structure |
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### Argument Instances |
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Each argument instance has the following attributes: |
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- `Argument ID`: The unique identifier for the argument within the dataset |
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- `Conclusion`: Conclusion text of the argument |
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- `Stance`: Stance of the `Premise` towards the `Conclusion; one of "in favor of", "against" |
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- `Premise`: Premise text of the argument |
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- `Labels`: The `Labels` for each example is an array of 1s (argument resorts to value) and 0s (argument does not resort to value). The order is the same as in the original files. |
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Additionally, the labels are separated into *value-categories*, aka. level 2 labels of the value taxonomy (Kiesel et al. 2022b), and *human values*, aka. level 1 labels of the value taxonomy. |
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This distinction is also reflected in the configuration names: |
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- `<config>`: As the [Task](https://touche.webis.de/semeval23/touche23-web/) is focused mainly on the detection of value-categories, |
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each base configuration ([listed below](#p-list-base-configs)) has the 20 value-categories as labels: |
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```python |
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labels = ["Self-direction: thought", "Self-direction: action", "Stimulation", "Hedonism", "Achievement", "Power: dominance", "Power: resources", "Face", "Security: personal", "Security: societal", "Tradition", "Conformity: rules", "Conformity: interpersonal", "Humility", "Benevolence: caring", "Benevolence: dependability", "Universalism: concern", "Universalism: nature", "Universalism: tolerance", "Universalism: objectivity"] |
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``` |
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- `<config>-level1`: The 54 human values from the level 1 of the value taxonomy are not used for the 2023 task |
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(except for the annotation), but are still listed here for some might find them useful for understanding the value |
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categories. Their order is also the same as in the original files. For more details see the [value-categories](#metadata-instances) configuration. |
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<p id="p-list-base-configs">The configuration names (as replacements for <code><config></code>) in this dataset are:</p> |
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- `main`: 8865 arguments (sources: `A`, `D`, `E`) with splits `train`, `validation`, and `test` (default configuration name) |
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```python |
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dataset_main_train = load_dataset("webis/Touche23-ValueEval", split="train") |
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dataset_main_validation = load_dataset("webis/Touche23-ValueEval", split="validation") |
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dataset_main_test = load_dataset("webis/Touche23-ValueEval", split="test") |
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``` |
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- `nahjalbalagha`: 279 arguments (source: `F`) with split `test` |
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```python |
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dataset_nahjalbalagha_test = load_dataset("webis/Touche23-ValueEval", name="nahjalbalagha", split="test") |
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``` |
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- `nyt`: 80 arguments (source: `G`) with split `test` |
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```python |
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dataset_nyt_test = load_dataset("webis/Touche23-ValueEval", name="nyt", split="test") |
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``` |
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- `zhihu`: 100 arguments (source: `C`) with split `validation` |
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```python |
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dataset_zhihu_validation = load_dataset("webis/Touche23-ValueEval", name="zhihu", split="validation") |
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``` |
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Please note that due to copyright reasons, there currently does not exist a direct download link to the arguments contained in the |
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New york Times |
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dataset. Accessing any of the `nyt` or `nyt-level1` configurations will therefore use the specifically created |
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[nyt-downloader program](https://github.com/touche-webis-de/touche-code/tree/main/semeval23/human-value-detection/nyt-downloader) |
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to create and access the arguments locally. See the program's |
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[README](https://github.com/touche-webis-de/touche-code/blob/main/semeval23/human-value-detection/nyt-downloader/README.md) |
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for further details. |
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### Metadata Instances |
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The following lists all configuration names for metadata. Each configuration only has a single split named `meta`. |
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- `ibm-meta`: Each row corresponds to one argument (IDs starting with `A`) from the [IBM-ArgQ-Rank-30kArgs](https://research.ibm.com/haifa/dept/vst/debating_data.shtml#Argument%20Quality) |
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- `Argument ID`: The unique identifier for the argument |
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- `WA`: the quality label according to the weighted-average scoring function |
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- `MACE-P`: the quality label according to the MACE-P scoring function |
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- `stance_WA`: the stance label according to the weighted-average scoring function |
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- `stance_WA_conf`: the confidence in the stance label according to the weighted-average scoring function |
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```python |
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dataset_ibm_metadata = load_dataset("webis/Touche23-ValueEval", name="ibm-meta", split="meta") |
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``` |
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- `zhihu-meta`: Each row corresponds to one argument (IDs starting with `C`) from the Chinese question-answering website [Zhihu](https://www.zhihu.com) |
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- `Argument ID`: The unique identifier for the argument |
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- `Conclusion Chinese`: The original chinese conclusion statement |
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- `Premise Chinese`: The original chinese premise statement |
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- `URL`: Link to the original statement the argument was taken from |
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```python |
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dataset_zhihu_metadata = load_dataset("webis/Touche23-ValueEval", name="zhihu-meta", split="meta") |
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``` |
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- `gdi-meta`: Each row corresponds to one argument (IDs starting with `D`) from [GD IDEAS](https://www.groupdiscussionideas.com/) |
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- `Argument ID`: The unique identifier for the argument |
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- `URL`: Link to the topic the argument was taken from |
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```python |
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dataset_gdi_metadata = load_dataset("webis/Touche23-ValueEval", name="gdi-meta", split="meta") |
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``` |
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- `cofe-meta`: Each row corresponds to one argument (IDs starting with `E`) from [the Conference for the Future of Europe](https://futureu.europa.eu) |
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- `Argument ID`: The unique identifier for the argument |
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- `URL`: Link to the comment the argument was taken from |
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```python |
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dataset_cofe_metadata = load_dataset("webis/Touche23-ValueEval", name="cofe-meta", split="meta") |
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``` |
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- `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`) |
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and 1047 additional arguments that were not labeled so far. This data was contributed by the language.ml lab. |
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- `Argument ID`: The unique identifier for the argument |
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- `Conclusion Farsi`: Conclusion text of the argument in Farsi |
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- `Stance Farsi`: Stance of the `Premise` towards the `Conclusion`, in Farsi |
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- `Premise Farsi`: Premise text of the argument in Farsi |
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- `Conclusion English`: Conclusion text of the argument in English (translated from Farsi) |
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- `Stance English`: Stance of the `Premise` towards the `Conclusion`; one of "in favor of", "against" |
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- `Premise English`: Premise text of the argument in English (translated from Farsi) |
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- `Source`: Source text of the argument; one of "Nahj al-Balagha", "Ghurar al-Hikam wa Durar ak-Kalim"; their Farsi translations were used |
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- `Method`: How the premise was extracted from the source; one of "extracted" (directly taken), "deduced"; the conclusion are deduced |
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```python |
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dataset_nahjalbalagha_metadata = load_dataset("webis/Touche23-ValueEval", name="nahjalbalagha-meta", split="meta") |
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``` |
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- `nyt-meta`: Each row corresponds to one argument (IDs starting with `G`) from [The New York Times](https://www.nytimes.com) |
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- `Argument ID`: The unique identifier for the argument |
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- `URL`: Link to the article the argument was taken from |
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- `Internet Archive timestamp`: Timestamp of the article's version in the Internet Archive that was used |
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```python |
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dataset_nyt_metadata = load_dataset("webis/Touche23-ValueEval", name="nyt-meta", split="meta") |
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``` |
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- `value-categories`: Contains a single JSON-entry with the structure of level 2 and level 1 values regarding the value taxonomy: |
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``` |
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{ |
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"<value category>": { |
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"<level 1 value>": [ |
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"<exemplary effect a corresponding argument might target>", |
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... |
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], ... |
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}, ... |
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} |
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``` |
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As this configuration contains just a single entry, an example usage could be: |
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```python |
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value_categories = load_dataset("webis/Touche23-ValueEval", name="value-categories", split="meta")[0] |
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``` |
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## Additional Information |
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### Dataset Curators |
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[More Information Needed] |
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### Licensing Information |
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[Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) |
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### Citation Information |
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``` |
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@Article{mirzakhmedova:2023a, |
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author = {Nailia Mirzakhmedova and Johannes Kiesel and Milad Alshomary and Maximilian Heinrich and Nicolas Handke\ |
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and Xiaoni Cai and Valentin Barriere and Doratossadat Dastgheib and Omid Ghahroodi and {Mohammad Ali} Sadraei\ |
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and Ehsaneddin Asgari and Lea Kawaletz and Henning Wachsmuth and Benno Stein}, |
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doi = {10.48550/arXiv.2301.13771}, |
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journal = {CoRR}, |
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month = jan, |
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publisher = {arXiv}, |
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title = {{The Touch{\'e}23-ValueEval Dataset for Identifying Human Values behind Arguments}}, |
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volume = {abs/2301.13771}, |
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year = 2023 |
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} |
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``` |
