Inscriptis -- A Python-based HTML to text conversion library optimized for knowledge extraction from the Web
Not on the map. Why?
Abstract (arXiv)
Inscriptis provides a library, command line client and Web service for converting HTML to plain text. Its development has been triggered by the need to obtain accurate text representations for knowledge extraction tasks that preserve the spatial alignment of text without drawing upon heavyweight, browser-based solutions such as Selenium. In contrast to related software packages, Inscriptis (i) provides a layout-aware conversion of HTML that more closely resembles the rendering obtained from standard Web browsers; and (ii) supports annotation rules, i.e., user-provided mappings that allow for annotating the extracted text based on structural and semantic information encoded in HTML tags and attributes. These unique features ensure that downstream knowledge extraction components can operate on accurate text representations, and may even use information on the semantics and structure of the original HTML document.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Jul 2021.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 1; 2025: 3; 2026: 2.
6 papers.
- 2025The Massive Legal Embedding Benchmark (MLEB)cited by 6
- 2024Cleaner Pretraining Corpus Curation with Neural Web Scrapingcited by 5
- 2026AXE: Low-Cost Cross-Domain Web Structured Information Extractioncited by 1
- 2026From Articles to Premises: Building PrimeFacts, an Extraction Methodology and Resource for Fact-Checking Evidencecited by 1
- 2025Scoring the Unscorables: Cyber Risk Assessment Beyond Internet Scanscited by 0
- 2025Cross-Domain Web Information Extraction at Pinterestcited by 0
- 2026From Articles to Premises: Building PrimeFacts, an Extraction Methodology and Resource for Fact-Checking Evidence7 May 2026
- 2026AXE: Low-Cost Cross-Domain Web Structured Information Extraction2 Feb 2026
- 2025The Massive Legal Embedding Benchmark (MLEB)22 Oct 2025
- 2025Cross-Domain Web Information Extraction at Pinterest1 Aug 2025
- 2025Scoring the Unscorables: Cyber Risk Assessment Beyond Internet Scans7 Jun 2025
- 2024Cleaner Pretraining Corpus Curation with Neural Web Scraping22 Feb 2024