Update README.md

README.md

@@ -15,12 +15,12 @@ CaT-Bench is a benchmark dataset designed to evaluate large language models' (LL
 
 ### Dataset Description
 
-CaT-Bench (Causal and Temporal Benchmark) is aimed at assessing the ability of language models to reason about causal and temporal relationships within natural language plans. The dataset is constructed from cooking recipes and contains 4,260 questions about causal dependencies spanning 57 unique plans. Each question asks whether a particular step in a recipe must occur before or after another step, challenging models to understand the underlying causal and temporal structure.
+CaT-Bench (Causal and Temporal Benchmark) is aimed at assessing the ability of language models to reason about causal and temporal relationships within natural language plans. The dataset is constructed from cooking recipes and contains 9,162 questions about causal dependencies spanning 300 unique plans. Each question asks whether a particular step in a recipe must occur before or after another step, challenging models to understand the underlying causal and temporal structure.
 
 - **Curated by:** Yash Kumar Lal*, Vanya Cohen*, Nathanael Chambers, Niranjan Balasubramanian, Raymond Mooney (* equal contribution)
 - **Funded by:** DARPA KAIROS program under agreement number FA8750-19-2-1003, National Science Foundation under award IIS #2007290, DARPA's Perceptually-enabled Task Guidance (PTG) program under Contract No. HR001122C007
 - **Language(s) (NLP):** English
-- **License:** Apache License 2.0
+- **License:** MIT License
 
 ### Dataset Sources