KnowGL: Knowledge Generation and Linking from Text
Gaetano Rossiello, Md. Faisal Mahbub Chowdhury, Nandana Mihindukulasooriya, Owen Cornec, Alfio Massimiliano Gliozzo
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.
BibTeX
@article{Rossiello_Chowdhury_Mihindukulasooriya_Cornec_Gliozzo_2024, title={KnowGL: Knowledge Generation and Linking from Text}, volume={37}, url={https://ojs.aaai.org/index.php/AAAI/article/view/27084}, DOI={10.1609/aaai.v37i13.27084}, abstractNote={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.}, number={13}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Rossiello, Gaetano and Chowdhury, Md. Faisal Mahbub and Mihindukulasooriya, Nandana and Cornec, Owen and Gliozzo, Alfio Massimiliano}, year={2024}, month={Jul.}, pages={16476-16478} }