Inscriptis -- A Python-based HTML to text conversion library optimized for knowledge extraction from the Web

TL;DR

Inscriptis is a Python library that converts HTML to accurate, layout-aware plain text suitable for knowledge extraction, supporting user-defined annotations based on HTML structure and semantics.

Contribution

It introduces a layout-aware HTML to text conversion method with annotation support, improving accuracy for knowledge extraction tasks over existing tools.

Findings

Provides more accurate text extraction resembling browser rendering.

Supports user-defined annotation rules for semantic information.

Enhances downstream knowledge extraction accuracy.

Abstract

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.