XISM: an eXploratory and Interactive Graph Tool to Visualize and Evaluate Semantic Map Models
Zhu Liu, Zhen Hu, Lei Dai, Yu Xuan, Ying Liu
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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 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 systemhttps://app.xism2025.xin/ , source codehttps://github.com/hank317/XISM , and demonstration videohttps://youtu.be/m5laLhGn6Ys are publicly available.