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arXiv · 2210.13952

KnowGL: Knowledge Generation and Linking from Text

Gaetano Rossiello·Md Faisal Mahbub Chowdhury·Nandana Mihindukulasooriya·Owen Cornec·Alfio Massimiliano Gliozzo
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Abstract

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.

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Gaetano Rossiello, Md Faisal Mahbub Chowdhury, Nandana Mihindukulasooriya, Owen Cornec, Alfio Massimiliano Gliozzo. 2022-10-25. KnowGL: Knowledge Generation and Linking from Text. https://arxiv.org/abs/2210.13952

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