Update README.md

README.md

@@ -1,92 +1,92 @@
----
-license: mit
-dataset_info:
-  features:
-  - name: annotation
-    dtype: string
-  - name: annotation_type
-    dtype: string
-  - name: annotator_id
-    dtype: string
-  - name: headline
-    dtype: string
-  - name: interval_end_at
-    dtype: int64
-  - name: interval_exact_highlight
-    dtype: string
-  - name: interval_start_at
-    dtype: int64
-  - name: lang
-    dtype: string
-  - name: text_id
-    dtype: int64
-  splits:
-  - name: all
-    num_bytes: 1150122
-    num_examples: 6027
-  - name: all_tags
-    num_bytes: 817638
-    num_examples: 4405
-  - name: gold_tags
-    num_bytes: 221311
-    num_examples: 1131
-  - name: spa_all_tags
-    num_bytes: 362800
-    num_examples: 2125
-  - name: spa_gold_tags
-    num_bytes: 102406
-    num_examples: 550
-  - name: ita_all_tags
-    num_bytes: 454838
-    num_examples: 2280
-  - name: ita_gold_tags
-    num_bytes: 118905
-    num_examples: 581
-  - name: all_comments
-    num_bytes: 111173
-    num_examples: 491
-  - name: spa_all_comments
-    num_bytes: 26572
-    num_examples: 151
-  - name: ita_all_comments
-    num_bytes: 84601
-    num_examples: 340
-  download_size: 685250
-  dataset_size: 3450366
-configs:
-- config_name: default
-  data_files:
-  - split: all
-    path: data/all-*
-  - split: all_tags
-    path: data/all_tags-*
-  - split: gold_tags
-    path: data/gold_tags-*
-  - split: spa_all_tags
-    path: data/spa_all_tags-*
-  - split: spa_gold_tags
-    path: data/spa_gold_tags-*
-  - split: ita_all_tags
-    path: data/ita_all_tags-*
-  - split: ita_gold_tags
-    path: data/ita_gold_tags-*
-  - split: all_comments
-    path: data/all_comments-*
-  - split: spa_all_comments
-    path: data/spa_all_comments-*
-  - split: ita_all_comments
-    path: data/ita_all_comments-*
-task_categories:
-- zero-shot-classification
-- question-answering
-- text-classification
-language:
-- es
-- it
-pretty_name: VIRC
-size_categories:
-- n<1K
----
+---
+license: mit
+dataset_info:
+  features:
+  - name: annotation
+    dtype: string
+  - name: annotation_type
+    dtype: string
+  - name: annotator_id
+    dtype: string
+  - name: headline
+    dtype: string
+  - name: interval_end_at
+    dtype: int64
+  - name: interval_exact_highlight
+    dtype: string
+  - name: interval_start_at
+    dtype: int64
+  - name: lang
+    dtype: string
+  - name: text_id
+    dtype: int64
+  splits:
+  - name: all
+    num_bytes: 1150122
+    num_examples: 6027
+  - name: all_tags
+    num_bytes: 817638
+    num_examples: 4405
+  - name: gold_tags
+    num_bytes: 221311
+    num_examples: 1131
+  - name: spa_all_tags
+    num_bytes: 362800
+    num_examples: 2125
+  - name: spa_gold_tags
+    num_bytes: 102406
+    num_examples: 550
+  - name: ita_all_tags
+    num_bytes: 454838
+    num_examples: 2280
+  - name: ita_gold_tags
+    num_bytes: 118905
+    num_examples: 581
+  - name: all_comments
+    num_bytes: 111173
+    num_examples: 491
+  - name: spa_all_comments
+    num_bytes: 26572
+    num_examples: 151
+  - name: ita_all_comments
+    num_bytes: 84601
+    num_examples: 340
+  download_size: 685250
+  dataset_size: 3450366
+configs:
+- config_name: default
+  data_files:
+  - split: all
+    path: data/all-*
+  - split: all_tags
+    path: data/all_tags-*
+  - split: gold_tags
+    path: data/gold_tags-*
+  - split: spa_all_tags
+    path: data/spa_all_tags-*
+  - split: spa_gold_tags
+    path: data/spa_gold_tags-*
+  - split: ita_all_tags
+    path: data/ita_all_tags-*
+  - split: ita_gold_tags
+    path: data/ita_gold_tags-*
+  - split: all_comments
+    path: data/all_comments-*
+  - split: spa_all_comments
+    path: data/spa_all_comments-*
+  - split: ita_all_comments
+    path: data/ita_all_comments-*
+task_categories:
+- zero-shot-classification
+- question-answering
+- text-classification
+language:
+- es
+- it
+pretty_name: VIRC
+size_categories:
+- n<1K
+---
 
 # Vulnerable Identities Recognition Corpus (VIRC) for Hate Speech Analysis
 Welcome to the Vulnerable Identities Recognition Corpus (VIRC), a dataset created to enhance hate speech analysis in Italian and Spanish news headlines. VIRC provides annotated headlines aimed at identifying vulnerable identities, dangerous discourse, derogatory mentions, and entities. This corpus contributes to developing more sophisticated hate speech detection tools and policies for creating a safer online environment.
@@ -104,17 +104,33 @@ VIRC is designed to support the study of hate speech in headlines from two langu
   - `Italian`: The Italian data consists of only one set annotated by two annotators.
 
 ## Annotation
-The `VIRC_Guidelines.pdf` contains the annotation guidelines provided to annotators. This can be seen sintetized in the paper. The dataset is provided with several split according to the following schema:
- - `all`: 
- - `all_tags`:
- - `gold_tags`:
- - `spa_all_tags`:
- - `spa_gold_tags`:
- - `ita_all_tags`:
- - `ita_gold_tags`: 
- - `all_comments`:
- - `spa_all_comments`:
- - `ita_all_comments`:
+The `VIRC_Guidelines.pdf` contains the annotation guidelines provided to annotators. This can be seen sintetized in the paper. The dataset is provided with several splits depending of which elements are included:
+ - `Annotations (Spanish)`: Annotators annotations for Spanish.
+ - `Annotations (Italian)`: Annotators annotations for Italian.
+ - `Gold (Spanish)`: Gold standard annotations for Spanish.
+ - `Gold (Italian)`: Gold standard annotations for Italian.
+ - `Comments (Spanish)`: Annotators comments for Spanish.
+ - `Comments (Italian)`: Annotators comments for Italian.
+
+The different splits include:
+
+| **Configuration**    | **Annotations (Spanish)** | **Annotations (Italian)** | **Gold (Spanish)** | **Gold (Italian)** | **Comments (Spanish)** | **Comments (Italian)** |
+|----------------------|---------------------------|---------------------------|--------------------|---------------------|------------------------|------------------------|
+| **`all`**            | ✅                        | ✅                        | ✅                 | ✅                  | ✅                     | ✅                     |
+| **`all_tags`**       | ✅                        | ✅                        | ✅                 | ✅                  | ❌                     | ❌                     |
+| **`gold_tags`**      | ❌                        | ❌                        | ✅                 | ✅                  | ❌                     | ❌                     |
+| **`tags`**           | ✅                        | ✅                        | ❌                 | ❌                  | ❌                     | ❌                     |
+| **`spa_all_tags`**   | ✅                        | ❌                        | ✅                 | ❌                  | ❌                     | ❌                     |
+| **`ita_all_tags`**   | ❌                        | ✅                        | ❌                 | ✅                  | ❌                     | ❌                     |
+| **`spa_tags`**       | ✅                        | ❌                        | ❌                 | ❌                  | ❌                     | ❌                     |
+| **`ita_tags`**       | ❌                        | ✅                        | ❌                 | ❌                  | ❌                     | ❌                     |
+| **`spa_gold_tags`**  | ❌                        | ❌                        | ✅                 | ❌                  | ❌                     | ❌                     |
+| **`ita_gold_tags`**  | ❌                        | ❌                        | ❌                 | ✅                  | ❌                     | ❌                     |
+| **`all_comments`**   | ❌                        | ❌                        | ❌                 | ❌                  | ✅                     | ✅                     |
+| **`spa_all_comments`**| ❌                        | ❌                        | ❌                 | ❌                  | ✅                     | ❌                     |
+| **`ita_all_comments`**| ❌                        | ❌                        | ❌                 | ❌                  | ❌                     | ✅                     |
+
+
 
 ## Acknowledgements
 This work is supported by the Predoctoral Grant (PIPF-2022/COM-25947) of the Consejería de Educación, Ciencia y Universidades de la Comunidad de Madrid, Spain. Arianna Longo's work has been supported by aequa-tech.