Update README.md

README.md

@@ -89,6 +89,8 @@ This dataset tests the capabilities of language models to correctly capture the
 We used probabilitic soft logic to combine probabilistic statements expressed with WEP (WEP-Reasoning) and we also used the UNLI dataset (https://nlp.jhu.edu/unli/) to directly check whether models can detect the WEP matching human-annotated probabilities.
 The dataset can be used as natural langauge inference data (context, premise, label) or multiple choice question answering (context,valid_hypothesis, invalid_hypothesis).
 
+
+Accepted at Starsem2023 (The 12th Joint Conference on Lexical and Computational Semantics). Temporary citation:
 ```bib
 @article{sileo2022probing,
   title={Probing neural language models for understanding of words of estimative probability},
@@ -97,4 +99,3 @@ The dataset can be used as natural langauge inference data (context, premise, la
   year={2022}
 }
 ```
-Accepted at Starsem2023 (The 12th Joint Conference on Lexical and Computational Semantics)