XISM: an eXploratory and Interactive Graph Tool to Visualize and Evaluate Semantic Map Models

TL;DR

XISM is an interactive tool that combines automated inference with expert input to create and refine semantic map models, enhancing transparency and scalability in linguistic analysis.

Contribution

It introduces a novel collaborative system that integrates data-driven methods with expert refinement for semantic map visualization.

Findings

Improves transparency in semantic map construction

Enhances controllability for linguists

Maintains computational efficiency

Abstract

Semantic map models visualize systematic relations among semantic functions through graph structures and are widely used in linguistic typology. However, existing construction methods either depend on labor-intensive expert reasoning or on fully automated systems lacking expert involvement, creating a tension between scalability and interpretability. We introduce \textbf{XISM}, an interactive system that combines data-driven inference with expert knowledge. XISM generates candidate maps via a top-down procedure and allows users to iteratively refine edges in a visual interface, with real-time metric feedback. Experiments in three semantic domains and expert interviews show that XISM improves linguistic decision transparency and controllability in semantic-map construction while maintaining computational efficiency. XISM provides a collaborative approach for scalable and interpretable semantic-map building. The system\footnote{https://app.xism2025.xin/} , source code\footnote{https://github.com/hank317/XISM} , and demonstration video\footnote{https://youtu.be/m5laLhGn6Ys} are publicly available.