Domain-aware extraction
Turn a Word table into structured JSON
Choose a document and analysis strategy. The server detects headers, understands column meaning, separates totals, and normalizes the records.
Ready to tryUse the controls above to interact with this demo.
What this demonstrates
Understand a table before extracting its cells
Positional extraction alone cannot reconcile headers such as MRN, Patient Number, or Medical Record Number. Domain-aware analysis maps those variations to a stable schema before records enter another system.
Key members
Load the Word document
ServerTextControl.Load
Enumerate tables
ServerTextControl.Tables
Read table structure
Table.Rows / Columns / Cells
Read cell values
TableCell.Text
How it works
The pipeline scores the first table rows against Financial, Healthcare, Manufacturing, and Generic vocabularies. It then detects the header row, canonicalizes each header, infers semantic types, and selects the most useful identifier column.
Rows are extracted with merged-cell handling. Amounts, percentages, and dates are converted to machine-friendly values, while subtotal and total rows are separated from ordinary records.
Automatic detection is the normal workflow. Explicit domain selection demonstrates how known business context can enforce a particular vocabulary and schema.
var analysis = new TableSemanticAnalyzer(options).Analyze(table);
var data = new TableJsonExtractor().Extract(table, analysis, options);
string json = data.ToJson();
Technique adapted from Extracting Structured Table Data from DOCX Word Documents.
NuGet packages
TXTextControl.TextControl.Core.SDK
34.0.4
Provides the core document model and server-side document processing APIs.
dotnet add package TXTextControl.TextControl.Core.SDK --version 34.0.4
Displays supported document and PDF formats in the browser.
dotnet add package TXTextControl.Web.DocumentViewer --version 34.2.0
