collections-template-generated-pages-delimiter-based-extraction-pattern-induced-handful-labelled CLM-0262For collections of template-generated pages, a delimiter-based extraction pattern induced from a handful of labelled examples can be reused across the rest of the collection, so extraction cost per page drops to pattern execution rather than per-page inference.
Capability: Writing a reusable locator: regex, SQL, XPath
Observed on
Holds when the documents share a rigid template so a small class of delimiter patterns suffices; breaks down on heterogeneous or free-form pages..
Sources
- Validated by: Not measured in the text available here; the source summary reports only that the approach learns and reuses wrappers and characterizes their efficiency and expressiveness.. Argued, not measured here: the source text is a second-hand summary with no numbers, no baseline, and no test set. The efficiency/expressiveness characterization is asserted rather than shown in what was provided.
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Related claims
- For structured extraction from text files, web pages and spreadsheets, a few user-highlighted example fields are enough to synthesise a reusable extraction program that pulls the remaining fields without further interaction — the locator can be inferred from examples rather than written or re-invoked per record.Writing a reusable locator: regex, SQL, XPath · reviewed by AI
- For synthesizing reusable XPath extractors from a few sampled web pages, a two-stage pipeline — first having a cheaper model extract both the target value and the neighbouring cue text from an attribute-stripped HTML tree, then having a stronger model write the XPath over HTML condensed around those located nodes with an execution-feedback loop — reaches usable extraction F1 on multi-domain product/listing pages while keeping prompt size far below feeding raw pages.Writing a reusable locator: regex, SQL, XPath · reviewed by AI
- When extracting structured rules from multimodal enterprise guideline documents, wrapping the extraction in deterministic schema validation, an LLM semantic judge, and a duplicate/contradiction consistency filter over a shared rule store lowers the share of extracted rules with no matching source sentence from about 15.7% to 3.2% relative to a one-pass pipeline using the same parser and models.Stating false facts confidently · reviewed by AI
- For extracting fields from vertical websites, decomposing XPath induction into separate sub-tasks over a few seed pages lets an LLM emit an XPath that generalizes to unseen pages of the same site, beating single-prompt CoT and Reflexion XPath generation by 14.84-23.86 F1 points, while calling the model only a handful of times instead of once per page.Writing a reusable locator: regex, SQL, XPath · reviewed by AI
- When retrieval for a summarization task pulls definitions by surface term match from a general encyclopedia, ambiguous terms fetch the wrong sense and the model incorporates that unsupported background into its output, lowering claim-level factuality below the no-retrieval baseline even when the prompt tells it to ignore unrelated retrieved content.Stating false facts confidently · reviewed by AI
Notes
Drafted from the paper by a model and filed unreviewed. Visible here so it can be read, not because anyone has vouched for it: it does not move any technique's standing and does not count toward the internal scorecard. Drafted confidence: low. Falsifier as drafted: Showing that induced delimiter wrappers, learned from a few examples of a template-generated collection, fail to extract correctly on most remaining pages of the same collection, so per-page extraction is still required.