ATLAS: Article Tracking, Linking, and Analysis of Swedish Encyclopedias

TL;DR

This paper presents ATLAS, a pipeline for restoring structure, categorizing, matching, and linking entries in digitized Swedish encyclopedias, enabling automated analysis of historical knowledge evolution.

Contribution

The work introduces a novel pipeline that extracts structure, categorizes, matches, and links encyclopedia entries across editions, with high accuracy.

Findings

Extracted headwords with 97.8% F1 score

Achieved 93.4% F1 in headword classification

Reached 93% precision in cross-edition matching

Abstract

The digitization of old encyclopedias represents an important step to improve access to historically structured knowledge. Often, however, this process does not go beyond an optical character recognition, leaving all the underlying structure unexploited. In addition, many encyclopedias had multiple editions reflecting the evolution of knowledge. The lack of structure in the raw text makes it difficult to track changes across these editions. In this work, we built a pipeline to restore the text structure, where we extract the headwords and identify entries; categorize the entities; match entries across editions; and link entries to a Wikidata item. We applied this pipeline to the four major editions of \textit{Nordisk familjebok}, an authoritative Swedish encyclopedia published between 1876 and 1951. We could extract the headwords with an F1 score of 97.8\% and we obtained an F1 score of 93.4\% on the headword classification. On a small-scale evaluation, we reached a 93\% precision on the cross-edition matching, 85\% precision and 16.5\% recall on the Wikidata linking. This shows that an automated approach to digitized historical knowledge is possible. This should facilitate the preservation of general knowledge and the understanding of knowledge transmission. The datasets and programs are available online.