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.argilla/dataset.json

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+{
+  "id": "fc15b1eb-1f70-4fe0-8612-7a1fc2082024",
+  "name": "human_baseline_zh",
+  "guidelines": "Please analyze the cultural style of the following advertising slogans and determine which slogan is more likely to be from Hong Kong and which is more likely to be from Mainland.",
+  "allow_extra_metadata": false,
+  "status": "ready",
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "metadata": null,
+  "workspace_id": "76348530-a335-4d00-b28a-1d21b0b3db29",
+  "last_activity_at": "2026-01-20T07:28:55.795072",
+  "inserted_at": "2026-01-20T06:09:02.899004",
+  "updated_at": "2026-01-20T06:09:05.022034"
+}

.argilla/settings.json

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+{
+  "guidelines": "Please analyze the cultural style of the following advertising slogans and determine which slogan is more likely to be from Hong Kong and which is more likely to be from Mainland.",
+  "allow_extra_metadata": false,
+  "distribution": {
+    "strategy": "overlap",
+    "min_submitted": 1
+  },
+  "fields": [
+    {
+      "id": "afd7a0cf-c844-4c82-b1ee-4f8f3b3a9d75",
+      "name": "Index",
+      "title": "Index",
+      "required": true,
+      "settings": {
+        "type": "text",
+        "use_markdown": false
+      },
+      "dataset_id": "fc15b1eb-1f70-4fe0-8612-7a1fc2082024",
+      "inserted_at": "2026-01-20T06:09:03.388399",
+      "updated_at": "2026-01-20T06:09:03.388399"
+    },
+    {
+      "id": "3004612d-6586-44be-9e64-3de11e87ce51",
+      "name": "Question",
+      "title": "Question",
+      "required": true,
+      "settings": {
+        "type": "text",
+        "use_markdown": false
+      },
+      "dataset_id": "fc15b1eb-1f70-4fe0-8612-7a1fc2082024",
+      "inserted_at": "2026-01-20T06:09:03.623350",
+      "updated_at": "2026-01-20T06:09:03.623350"
+    }
+  ],
+  "questions": [
+    {
+      "id": "4a9470dd-5091-4e45-a058-1e4e76917825",
+      "name": "A Style",
+      "title": "A Style",
+      "description": null,
+      "required": true,
+      "settings": {
+        "type": "label_selection",
+        "options": [
+          {
+            "value": "HK",
+            "text": "HK",
+            "description": null
+          },
+          {
+            "value": "CN",
+            "text": "CN",
+            "description": null
+          },
+          {
+            "value": "Cannot Determine",
+            "text": "Cannot Determine",
+            "description": null
+          }
+        ],
+        "visible_options": 3
+      },
+      "dataset_id": "fc15b1eb-1f70-4fe0-8612-7a1fc2082024",
+      "inserted_at": "2026-01-20T06:09:04.520649",
+      "updated_at": "2026-01-20T06:09:04.520649"
+    },
+    {
+      "id": "ee8d202a-7231-4da4-b5f7-dfc349c83bae",
+      "name": "B Style",
+      "title": "B Style",
+      "description": null,
+      "required": true,
+      "settings": {
+        "type": "label_selection",
+        "options": [
+          {
+            "value": "HK",
+            "text": "HK",
+            "description": null
+          },
+          {
+            "value": "CN",
+            "text": "CN",
+            "description": null
+          },
+          {
+            "value": "Cannot Determine",
+            "text": "Cannot Determine",
+            "description": null
+          }
+        ],
+        "visible_options": 3
+      },
+      "dataset_id": "fc15b1eb-1f70-4fe0-8612-7a1fc2082024",
+      "inserted_at": "2026-01-20T06:09:04.769707",
+      "updated_at": "2026-01-20T06:09:04.769707"
+    }
+  ],
+  "metadata": [],
+  "vectors": []
+}

.argilla/version.json

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+{
+  "argilla": "2.8.0"
+}

README.md

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 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: status
-    dtype: string
-  - name: inserted_at
-    dtype: timestamp[us]
-  - name: updated_at
-    dtype: timestamp[us]
-  - name: _server_id
-    dtype: string
-  - name: Index
-    dtype: string
-  - name: Question
-    dtype: string
-  - name: A Style.responses
-    sequence: string
-  - name: A Style.responses.users
-    sequence: string
-  - name: A Style.responses.status
-    sequence: string
-  - name: B Style.responses
-    sequence: string
-  - name: B Style.responses.users
-    sequence: string
-  - name: B Style.responses.status
-    sequence: string
-  splits:
-  - name: train
-    num_bytes: 1275140
-    num_examples: 1078
-  download_size: 648489
-  dataset_size: 1275140
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+tags:
+- rlfh
+- argilla
+- human-feedback
 ---
+
+# Dataset Card for human_baseline_zh
+
+
+
+
+
+
+
+This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets).
+
+
+## Using this dataset with Argilla
+
+To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code:
+
+```python
+import argilla as rg
+
+ds = rg.Dataset.from_hub("Jessie09/human_baseline_zh", settings="auto")
+```
+
+This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation.
+
+## Using this dataset with `datasets`
+
+To load the records of this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("Jessie09/human_baseline_zh")
+```
+
+This will only load the records of the dataset, but not the Argilla settings.
+
+## Dataset Structure
+
+This dataset repo contains:
+
+* Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`.
+* The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla.
+* A dataset configuration folder conforming to the Argilla dataset format in `.argilla`.
+
+The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**.
+
+### Fields
+
+The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset.
+
+| Field Name | Title | Type | Required |
+| ---------- | ----- | ---- | -------- |
+| Index | Index | text | True |
+| Question | Question | text | True |
+
+
+### Questions
+
+The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking.
+
+| Question Name | Title | Type | Required | Description | Values/Labels |
+| ------------- | ----- | ---- | -------- | ----------- | ------------- |
+| A Style | A Style | label_selection | True | N/A | ['HK', 'CN', 'Cannot Determine'] |
+| B Style | B Style | label_selection | True | N/A | ['HK', 'CN', 'Cannot Determine'] |
+
+
+<!-- check length of metadata properties -->
+
+
+
+
+### Data Splits
+
+The dataset contains a single split, which is `train`.
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation guidelines
+
+Please analyze the cultural style of the following advertising slogans and determine which slogan is more likely to be from Hong Kong and which is more likely to be from Mainland.
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]
+
+### Contributions
+
+[More Information Needed]