Principle:Ucbepic Docetl LLM Powered Text Extraction
| Knowledge Sources | |
|---|---|
| Domains | LLM_Data_Processing, Information_Extraction |
| Last Updated | 2026-02-08 00:00 GMT |
Overview
Guided text extraction uses an LLM to identify and locate specific passages within unstructured documents, returning the exact source text rather than a generated summary or transformation.
Theoretical Basis
Many information extraction tasks require pinpointing specific passages within a document rather than transforming or summarizing the entire content. For example, extracting the "methods" section from a research paper, finding relevant clauses in a legal contract, or locating error messages in log files. Unlike map operations that produce new content, extraction operations identify and return verbatim text from the original document. This distinction is critical for tasks where provenance and exact wording matter.
DocETL's extract operation implements two extraction strategies. The line-number strategy reformats the document text into numbered lines of fixed width, presents these numbered lines to the LLM along with extraction instructions, and asks the LLM to return start_line/end_line ranges identifying the relevant passages. The extracted text is then reconstructed from the original numbered lines, stripping the line number prefixes. The regex strategy asks the LLM to generate Python-compatible regular expressions that match the desired content, then applies those patterns to the original text using re.findall. Both strategies produce a list of extracted text fragments per document key.
The two-strategy design reflects a fundamental trade-off: line-number extraction is more robust for long documents and complex passage boundaries (the LLM only needs to identify positions, not craft patterns), while regex extraction is more precise for structured content with consistent formatting. Both strategies are executed through the same parallel processing framework, with configurable error handling (skip or raise) and support for multiple document keys per input record. Results are deduplicated and can be returned as either a concatenated string or a list of fragments.
Key Design Decisions
| Decision | Choice | Rationale |
|---|---|---|
| Extraction method | Two strategies: line-number ranges and LLM-generated regex patterns | Line numbers are robust for free-form text; regex is precise for structured content; users choose based on document characteristics |
| Line formatting | Fixed-width lines with numeric prefixes (e.g., "0001: text") | Gives the LLM unambiguous positional references; fixed width prevents line-count confusion from varying line lengths |
| Output handling | Deduplication of extracted fragments with optional concatenation or list output | Prevents duplicate extractions when multiple line ranges or patterns overlap; format choice supports different downstream needs |