TiFi: Taxonomy Induction for Fictional Domains

Taxonomies are important building blocks of structured knowledge bases, and their construction from text sources and Wikipedia has received much attention. In this project, we focus on the construction of taxonomies for fictional domains, using noisy category systems from fan wikis or text extraction as input. Such fictional domains are archetypes of entity universes that are poorly covered by Wikipedia, such as also enterprise-specific knowledge bases or highly specialized verticals.

Our fiction-targeted approach, called TiFi, consists of three phases: (i) category cleaning, by identifying candidate categories that truly represent classes in the domain of interest, (ii) edge cleaning, by selecting subcategory relationships that correspond to class subsumption, and (iii) top-level construction, by mapping classes onto a subset of high-level WordNet categories.

TiFi is able to construct taxonomies for a diverse range of fictional domains such as Lord of the Rings, The Simpsons or Greek Mythology with very high precision.

Resources

Data

Final taxonomies of six universes (GoT, LoTR, Simpsons, Starwars, Greekmytholgoy and game World of Warcraft) can be found here.

 

Paper

TiFi: Taxonomy Induction for Fictional Domains (short paper)
Cuong Xuan Chu, Simon Razniewski, Gerhard Weikum
In Proc. WWW 2019

TiFi: Taxonomy Induction for Fictional Domains​​​​​​​ (extended version)
Cuong Xuan Chu, Simon Razniewski, Gerhard Weikum
In arXiv​​​​​​​