Published on Tue Oct 25 2022
KnowGL: Knowledge Generation and Linking from Text
See More ...
We propose KnowGL, a tool that allows converting text into structured
relational data represented as a set of ABox assertions compliant with the TBox
of a given Knowledge Graph (KG), such as Wikidata. We address this problem as a
sequence generation task by leveraging pre-trained sequence-to-sequence
language models, e.g. BART. Given a sentence, we fine-tune such models to
detect pairs of entity mentions and jointly generate a set of facts consisting
of the full set of semantic annotations for a KG, such as entity labels, entity
types, and their relationships. To showcase the capabilities of our tool, we
build a web application consisting of a set of UI widgets that help users to
navigate through the semantic data extracted from a given input text. We make
the KnowGL model available at https://huggingface.co/ibm/knowgl-large.
2
89
356