To maintain document structure like sections and clauses in vector form, you need to explicitly encode hierarchical relationships and positional context alongside the text content. This involves breaking the document into logical units (e.g., sections, clauses), preserving metadata about their order and nesting, and using techniques that retain this information during vectorization. For example, a legal contract might be split into clauses with identifiers like “Section 3.2(a),” and each unit is embedded while tracking its place in the document’s outline.
One practical approach is to preprocess the document into structured chunks before vectorization. Each chunk (e.g., a clause or subsection) is stored with metadata like its section number, parent section, and depth in the hierarchy. When generating vectors, you can use models that preserve positional context, such as transformers with positional encoding, or append structural tags (e.g., "[SECTION_3.2]") to the text before embedding. For example, a clause starting with “Termination Rights:…” could be prefixed with "[CLAUSE_5.1]" to signal its position. Vector databases like FAISS or Pinecone can then store these vectors alongside their metadata, enabling queries that consider both semantic meaning and structural context.
Another strategy involves using graph-based representations. Each section or clause becomes a node in a graph, with edges representing parent-child relationships (e.g., Section 3 contains Subsection 3.1). Nodes can be embedded using graph neural networks (GNNs) or have their text content vectorized independently while storing adjacency information separately. For instance, a vector for “Clause 4.2” might link to its parent “Section 4” via metadata. This allows retrieval systems to reconstruct the document’s hierarchy during search or analysis. Tools like LangChain’s hierarchical document loaders or custom parsers can automate splitting and tagging, ensuring the vectorization pipeline retains structural signals critical for tasks like contract analysis or regulatory compliance checks.