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README.md

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----
-license: cc-by-nc-4.0
-dataset_info:
-  features:
-  - name: scene_id
-    dtype: string
-  - name: dialogue
-    dtype: string
-  - name: relation_high_probable_gold
-    dtype: string
-  - name: relation_impossible_gold
-    dtype: string
-  - name: high_probable_agreement
-    dtype: string
-  - name: intimacy_gold
-    dtype: string
-  - name: intimacy_agreement
-    dtype: string
-  - name: formality_gold
-    dtype: string
-  - name: formality_agreement
-    dtype: string
-  - name: hierarchy_gold
-    dtype: string
-  - name: hierarchy_agreement
-    dtype: string
-  - name: age-a_gold
-    dtype: string
-  - name: age-b_gold
-    dtype: string
-  - name: age_diff_gold
-    dtype: string
-  - name: gender-a_gold
-    dtype: string
-  - name: gender-b_gold
-    dtype: string
-  - name: gender_diff_gold
-    dtype: string
-  splits:
-  - name: en
-    num_bytes: 891609
-    num_examples: 580
-  - name: ko
-    num_bytes: 871114
-    num_examples: 567
-  download_size: 646225
-  dataset_size: 1762723
-configs:
-- config_name: default
-  data_files:
-  - split: en
-    path: data/en-*
-  - split: ko
-    path: data/ko-*
----
+---
+license: cc-by-nc-nd-4.0
+task_categories:
+- text-classification
+- question-answering
+language:
+- en
+- ko
+tags:
+- social-reasoning
+- dialogue
+- relation-classification
+- conversation-analysis
+size_categories:
+- n<1K
+---
+
+<div align="center">
+  <h1> Are they lovers or friends? Evaluating LLMs' Social Reasoning in English and Korean Dialogues </h1>
+  <p>
+    <a href="https://arxiv.org/pdf/2510.19028">
+      <img src="https://img.shields.io/badge/ArXiv-SCRIPTS-red" alt="Paper">
+    </a>
+    <a href="https://github.com/rladmstn1714/SCRIPTS">
+      <img src="https://img.shields.io/badge/GitHub-Code-blue" alt="GitHub">
+    </a>
+    <a href="https://huggingface.co/datasets/EunsuKim/SCRIPTS">
+      <img src="https://img.shields.io/badge/🤗_HuggingFace-Dataset-yellow" alt="Hugging Face">
+    </a>
+  </p>
+</div>
+
+**Official dataset for [Are they lovers or friends? Evaluating LLMs' Social Reasoning in English and Korean Dialogues](https://arxiv.org/pdf/2510.19028).**
+
+## Dataset Description
+
+SCRIPTS is a bilingual dialogue dataset for evaluating social reasoning capabilities of Large Language Models. The dataset contains dialogues with rich annotations about relationships, social dimensions, and demographic attributes.
+
+### Dataset Splits
+
+- **`en`**: 580 English dialogues
+- **`ko`**: 567 Korean dialogues
+
+### Languages
+
+- English
+- Korean (한국어)
+
+## Dataset Structure
+
+### Data Fields
+
+Each example contains the following fields:
+
+#### Core Fields
+- `scene_id` (string): Unique identifier for each dialogue
+- `dialogue` (string): Conversation text with speaker markers `[A]:` and `[B]:`
+
+#### Relation Classification
+- `relation_high_probable_gold` (string): Ground truth high-probability social relation
+- `relation_impossible_gold` (string): Relations annotated as impossible/unlikely
+- `high_probable_agreement` (string): Inter-annotator agreement level
+
+#### Social Dimensions
+- `intimacy_gold` (string): Intimacy level (intimate, not intimate, neutral, unknown)
+- `intimacy_agreement` (float): Inter-annotator agreement score
+- `formality_gold` (string): Formality/task orientation (formal, informal, neutral, unknown)
+- `formality_agreement` (float): Inter-annotator agreement score
+- `hierarchy_gold` (string): Power dynamics (equal, hierarchical, unknown)
+- `hierarchy_agreement` (float): Inter-annotator agreement score
+
+#### Demographics
+- `age-a_gold` (string): Age category for speaker A
+- `age-b_gold` (string): Age category for speaker B
+- `age_diff_gold` (string): Age comparison (A>B, A<B, A=B, Unknown)
+- `gender-a_gold` (string): Gender for speaker A
+- `gender-b_gold` (string): Gender for speaker B
+- `gender_diff_gold` (string): Gender comparison (Same, Different, Unknown)
+
+### Data Example
+
+**English (`en` split):**
+```python
+{
+  'scene_id': 'scene300',
+  'dialogue': '[B]: [A], right? Happy to meet you.\n[A]: Officially almost human again...',
+  'relation_high_probable_gold': "{'rank1': {'Police-Victim': 0.67, 'Police officer-Civilian': 0.33}, ...}",
+  'intimacy_gold': 'Unintimate',
+  'formality_gold': 'Task-oriented',
+  'hierarchy_gold': 'A<B',
+  'age-a_gold': "['(20–35) Young adult']",
+  'gender-a_gold': "['Cannot be determined']",
+  ...
+}
+```
+
+**Korean (`ko` split):**
+```python
+{
+  'scene_id': '0',
+  'dialogue': 'B: 눈깔 안 돌리면 뽑아서 골프공으로 쓴다!...고 속으로 말했습니다...',
+  'relation_high_probable_gold': "['친구', '성직자-신도', '지인']",
+  'intimacy_gold': '친함',
+  'formality_gold': '즐거움 중심',
+  'hierarchy_gold': 'A=B',
+  'age-a_gold': "['대학생(20-24)', '청년(25-39)', '중장년(40-59)', '노년(65-)']",
+  'gender-a_gold': "['남성', '여성']",
+  ...
+}
+```
+
+## Usage
+
+### Loading the Dataset
+
+```python
+from datasets import load_dataset
+
+# Load both splits
+dataset = load_dataset('EunsuKim/SCRIPTS')
+
+# Access English dialogues
+en_data = dataset['en']
+print(f"English samples: {len(en_data)}")
+
+# Access Korean dialogues
+ko_data = dataset['ko']
+print(f"Korean samples: {len(ko_data)}")
+
+# View a sample
+print(en_data[0])
+```
+
+### Loading Specific Split
+
+```python
+# Load only English
+en_dataset = load_dataset('EunsuKim/SCRIPTS', split='en')
+
+# Load only Korean
+ko_dataset = load_dataset('EunsuKim/SCRIPTS', split='ko')
+```
+
+### Example: Filtering by Relation Type
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset('EunsuKim/SCRIPTS', split='en')
+
+# Filter dialogues with high intimacy
+intimate_dialogues = dataset.filter(lambda x: 'intimate' in x['intimacy_gold'].lower())
+print(f"Found {len(intimate_dialogues)} intimate dialogues")
+```
+
+## Dataset Creation
+
+### Source Data
+
+The dialogues were collected from various English and Korean sources and annotated by multiple annotators for:
+- Social relations (e.g., friends, colleagues, parent-child)
+- Social dimensions (intimacy, formality, hierarchy)
+- Demographic attributes (age, gender)
+
+### Annotations
+
+Multiple annotators labeled each dialogue, and inter-annotator agreement scores are provided. The `_gold` suffix indicates gold standard annotations, while `_agreement` fields show annotator consensus levels.
+
+## Considerations for Using the Data
+
+### Social Impact
+
+This dataset is designed to evaluate and improve LLMs' understanding of social relationships in conversations. It can help:
+- Assess cultural differences in social reasoning between English and Korean
+- Evaluate model performance on nuanced social understanding tasks
+- Develop culturally-aware conversational AI systems
+
+### Limitations
+
+- Limited to dyadic (two-person) conversations
+- Focuses on specific social dimensions and may not capture all aspects of social reasoning
+- Annotations reflect cultural norms of the annotation team
+- Some dialogues may have multiple valid interpretations
+
+## License
+
+**CC-BY-NC-ND 4.0** (Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International)
+
+## Citation
+
+```bibtex
+@misc{kim2025loversfriendsevaluatingllms,
+      title={Are they lovers or friends? Evaluating LLMs' Social Reasoning in English and Korean Dialogues}, 
+      author={Eunsu Kim and Junyeong Park and Juhyun Oh and Kiwoong Park and Seyoung Song and A. Seza Dogruoz and Najoung Kim and Alice Oh},
+      year={2025},
+      eprint={2510.19028},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2510.19028}, 
+}
+```
+
+## Contact
+
+For questions or issues, please:
+- Open an issue on [GitHub](https://github.com/rladmstn1714/SCRIPTS)
+- Refer to the [paper](https://arxiv.org/pdf/2510.19028) for detailed methodology
+