Initial project scaffold

Sets up directory structure for 6-person team split: data, src, evaluation,
analysis, report, notebooks. Each person owns one top-level directory.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*.pyo
+*.pyd
+.Python
+*.egg-info/
+dist/
+build/
+*.egg
+
+# Environments
+.env
+.venv
+venv/
+env/
+
+# Jupyter
+.ipynb_checkpoints/
+*.ipynb_checkpoints
+
+# Data — raw files are not committed; only processed artifacts are
+data/raw/
+data/cache/
+*.csv
+*.jsonl
+*.parquet
+*.pkl
+
+# Secrets (Reddit API credentials etc.)
+.env
+*.env
+
+# IDEs
+.vscode/
+.idea/
+*.swp
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Model checkpoints (large binaries)
+checkpoints/
+*.pt
+*.bin
+*.safetensors

README.md

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+# Argument Mining for Online Debates
+
+NLP group project — Option 1: Application Development.
+
+Given a Reddit thread where people disagree, the system extracts argument structure (claims, counter-claims, premises) and surfaces what the debate is actually about.
+
+## Project structure
+
+```
+nlp-project/
+├── data/               # Data loading and preprocessing (Person 1)
+├── src/                # Models and inference pipeline (Person 2)
+├── evaluation/         # Custom eval harness and metrics (Person 3)
+├── analysis/           # Failure mode analysis (Person 4)
+├── report/             # Literature review and written report (Person 5)
+└── notebooks/          # Exploration and demos (Person 6)
+```
+
+## Setup
+
+```bash
+python -m venv venv
+source venv/bin/activate
+pip install -r requirements.txt
+```
+
+Copy `.env.example` to `.env` and fill in your Reddit API credentials before using the Reddit scraper.
+
+## Data sources
+
+- **Change My View (CMV)** — r/changemyview threads with delta annotations as persuasion signals
+- **IBM Debater** — `ibm/argument_quality_ranking_30k` via HuggingFace datasets
+- **Live Reddit** — PRAW scraper for fresh threads
+
+See `data/README.md` for details on obtaining and placing raw files.
+
+## Use of AI tools
+
+This project used LLMs (Claude) for boilerplate code generation and literature search. All methodology decisions, test set design, label definitions, and conclusions are the team's own.

requirements.txt

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+datasets>=2.14.0
+transformers>=4.35.0
+torch>=2.0.0
+pandas>=2.0.0
+numpy>=1.24.0
+praw>=7.7.0
+scikit-learn>=1.3.0
+tqdm>=4.66.0
+python-dotenv>=1.0.0