Discovering Fine-Grained Semantics in Knowledge Graph Relations

Talk by Nitisha Jain

Location: APB room 3027
Start: 6. October 2022 at 11:00 am
End: 6. October 2022 at 12:00 pm
Event series: Research Seminar Logic and AI
iCal

Knowledge graphs (KGs) provide structured representation of data in the

form of relations between different entities. The semantics of relations between words and entities are often ambiguous, where it is common to find polysemous relations that represent multiple semantics based on the context. This ambiguity in relation semantics also proliferates KG triples. While the guidance from custom-designed ontologies addresses this issue to some extent, our analysis shows that the heterogeneity and complexity of real-world data still results in substantial relation polysemy within popular KGs. The correct semantic interpretation of KG relations is necessary for many downstream applications such as entity classification and question answering.

We present the problem of fine-grained relation discovery and a data-driven method towards this task that leverages the vector representations of the knowledge graph entities and relations available from relational learning models.

We show that by performing clustering over these vectors, our method is able to not only identify the polysemous relations in knowledge graphs, but also discover the different semantics associated with them. Extensive empirical evaluation shows that fine-grained relations discovered by the proposed approach lead to substantial improvement in the semantics in the Yago and NELL datasets, as compared to baselines.

The talk will take place in a hybrid fashion, physically in the seminar room, and online through the link:

https://bbb.tu-dresden.de/b/pio-zwt-smp-aus