The syntactic structure of a sentence can be described as a tree that indicates the syntactic relationships between words. In spite of significant progress in unsupervised methods that retrieve the syntactic structure of sentences, guessing the right direction of edges is still a challenge. As in a syntactic dependency structure edges are oriented away from the root, the challenge of guessing the right direction can be reduced to finding an undirected tree and the root. The limited performance of current unsupervised methods demonstrates the lack of a proper understanding of what a root vertex is from first principles. We consider an ensemble of centrality scores, some that only take into account the free tree (non-spatial scores) and others that take into account the position of vertices (spatial scores). We test the hypothesis that the root vertex is an important or central vertex of the syntactic dependency structure. We confirm the hypothesis in the sense that root vertices tend to have high centrality and that vertices of high centrality tend to be roots. The best performance in guessing the root is achieved by novel scores that only take into account the position of a vertex and that of its neighbours. We provide theoretical and empirical foundations towards a universal notion of rootness from a network science perspective.

翻译：句子的句法结构可描述为表示词间句法关系的树结构。尽管无监督方法在获取句子句法结构方面取得显著进展，但准确推断边的方向仍具挑战性。由于句法依存结构中的边由根节点向外指向，推断方向的问题可简化为寻找无向树及其根节点。当前无监督方法的有限性能表明，从第一性原理角度对根节点本质的理解尚不充分。我们考虑一组中心性指标集合，其中部分仅考虑自由树结构（非空间指标），另一部分则纳入顶点位置信息（空间指标）。我们检验以下假设：根节点是句法依存结构中重要或中心的顶点。从根节点倾向于具有高中心性、且高中心性顶点倾向于作为根节点两方面，该假设得到证实。猜测根节点的最佳性能由仅考虑顶点及其邻接点位置的新型指标实现。我们从网络科学视角为根节点属性的普适性概念提供了理论与实证基础。