Goal: Participants will develop machine learning models to accurately translate natural language questions, combined with a Neo4j graph schema, into executable Cypher queries.

Key Difficulty: Evaluating the correctness of generated code (Cypher queries) is much harder than evaluating numerical predictions.

Impact: This challenge aims to advance the state-of-the-art in natural language to graph query generation, making graph databases more accessible and powerful for a wider audience.