Update README.md
The reported results do not match what is written in the paper.
The paper reported a micro F1 Score.
A 70% micro F1 Score on the REBEL Dataset would also not be SOTA, since REBEL achieved 74 micro-F1 Score (Section 5 in https://aclanthology.org/2021.findings-emnlp.204.pdf)
We evaluated the KnowGL model using the experimental setup described in the GenIE paper (Table 1 https://aclanthology.org/2022.naacl-main.342.pdf) where the F1 is 68.93.
Details about KnowGL evaluation are described in the paper https://arxiv.org/abs/2207.05188, that's already mentioned in the current README.md
@mingaflo The evaluation done by the REBEL authors is not the same as the one done by the GenIE authors and by us. Please look at Figure 1 in https://aclanthology.org/2021.findings-emnlp.204.pdf and compare it with the Figure 1 in https://aclanthology.org/2022.naacl-main.342.pdf . The extracted triples do not contain same kind of information.
Given a text "US president Biden was born in Pennsylvania", the REBEL system is expected to generate "<Biden, position held, US president>" or "<US, president, Biden>". Here "US" and "Biden" are entity mentions which are already inside the text.
But the GenIE system (and our KnowGL system) is expected to generate "<Joe Biden, position held, President of the United States>" or "<United States of America, president, Joe Biden>". "United States of America" and "Joe Biden" are corresponding Wikidata labels for those entities, and are not necessarily inside the text.
Hope this clarifies any confusion.
Thanks for clarifying!