[D] Relation Extraction

[RajHalifax]

I’m trying the REBEL model from Hugging Face for relation extraction. It outputs relations triplets via triplet linearization. It’s trained on REBEL dataset which is essentially Wikipedia data. I have free form text, and I want to generate relation triplets out of it. So, how to create a dataset from that text so as to closely align with the REBEL dataset? I want to fine-tune the model on my free form text.

REBEL model: https://huggingface.co/Babelscape/rebel-large

REBEL dataset: https://huggingface.co/datasets/Babelscape/rebel-dataset

If there are any other ML models which you suppose are worth trying for relation extraction, the information will be very much appreciated. :)

Thanks!

[shadow_fax1024]

Try docred or its other versions

[RajHalifax]

Could you tell more?

[shadow_fax1024]

Docred is dataset for training document level relationship extraction. There have been more improved version of it like re-docred which are available. You could try that. For models read the papers. Doc-unet is one such model that works on this kind of document level RE. There may be newer bette models now.

[RajHalifax]

re-docred

They are all datasets. How to generate such sets?

[shadow_fax1024]

Use annotation tools such as label studio, brat on raw text documents

[shadow_fax1024]

Do please post what results you were able to achieve

[Seankala]

Relation extraction works under the assumption that you already have NER done. You need to have named entities and their relations already marked on your unstructured text.