ConfliBERT GUI

A browser-based NLP toolkit for conflict and political violence text analysis. Built on ConfliBERT, the GUI provides an accessible interface for named entity recognition, text classification, question answering, and model fine-tuning, with no coding required.

GitHub | Developed with Sultan Alsarra

Features

Named Entity Recognition: Identify organizations, persons, locations, weapons, and temporal expressions in conflict text
Binary Classification: Determine if text describes a conflict event, with confidence scores
Multilabel Classification: Categorize text into event types: Armed Assault, Bombing/Explosion, Kidnapping, Other
Question Answering: Extract answers from conflict-related passages
Fine-Tuning: Train custom classifiers with LoRA/QLoRA on your own data, with seven base architectures
Batch Processing: Upload CSVs for bulk analysis

Walkthrough

Home

The landing page lets you select your task and input text directly or upload a CSV for batch processing.

ConfliBERT GUI home screen

Named Entity Recognition

Paste any conflict-related text and the model identifies and color-codes named entities: persons, organizations, locations, weapons, and more.

NER results with color-coded entities

Text Classification

Binary classification determines whether text describes a conflict event. Results include confidence scores for each class.

Binary classification results with confidence scores

Multilabel Classification

Each text is scored against four event categories independently, useful for texts describing multiple event types.

Multilabel classification showing multiple event type scores

Question Answering

Enter a passage and a question. The model extracts the relevant answer span directly from the text.

Question answering extracting answers from context

Fine-Tuning

Train custom classifiers on your labeled data. Select a base model, upload training/validation sets, configure hyperparameters, and monitor training progress.

Fine-tuning interface with model selection and training parameters

Installation

# Clone the repository
git clone https://github.com/shreyasmeher/conflibert-gui.git
cd conflibert-gui

# Create virtual environment
python -m venv env
source env/bin/activate  # Mac/Linux
# env\Scripts\activate   # Windows

# Install dependencies
pip install -r requirements.txt

# Run
python app.py
# Open http://localhost:7860

Requirements: Python 3.8+, PyTorch, Transformers, Gradio

Models

Task	Model
NER	`eventdata-utd/conflibert-named-entity-recognition`
Binary Classification	`eventdata-utd/conflibert-binary-classification`
Multilabel	`eventdata-utd/conflibert-satp-relevant-multilabel`
Question Answering	`salsarra/ConfliBERT-QA`

Citation

@inproceedings{hu2022conflibert,
  title={ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence},
  author={Hu, Yibo and Hosseini, MohammadSaleh and Parolin, Erick Skorupa
          and Osorio, Javier and Khan, Latifur and Brandt, Patrick and D'Orazio, Vito},
  booktitle={Proceedings of NAACL-HLT 2022},
  pages={5469--5482},
  year={2022}
}