Propagate changes to dataset card

README.md

@@ -11,7 +11,7 @@ GitGoodBench Lite is a subset of 900 samples for evaluating the performance of A
 The samples in the dataset are evenly split across the programming languages Python, Java and Kotlin and the sample types merge conflict resolution and file-commit gram.
 This dataset thus contains 150 samples per sample type and programming language.
 
-All data in this dataset are collected from 493 unique, open-source GitHub repositories with permissive licenses 
+All data in this dataset are collected from 479 unique, open-source GitHub repositories with permissive licenses 
 that have >= 1000 stars, >= 5 branches, >= 10 contributors and are not a fork or archived. We collected the initial list of repositories using [SEART.](https://seart-ghs.si.usi.ch/)
 
 Evaluation is to be performed by exact-match (EM) of diffs for the merge conflict setting and by LLM-as-a-Judge for the file-commit gram setting. [For further details see our paper.]()
@@ -43,7 +43,8 @@ File-commit chain scenarios consist of two commits, the oldest and newest commit
 In total the chain consists of `times_seen_consecutively` commits. The intended use-cases of these scenarios are to evaluate the agent's capacity to create meaningful, cohesive commits or 
 improve the local tree via rebasing. Thus samples of this `sample_type` cover two scenario types.
 
-File-commit chains are at least 3 commits long, all commits only contain files in the specified programming_language and no commit is a merge commit.
+File-commit chains are at least 3 commits long,the file the sample concerns itself with is guaranteed to be of `programming_language`
+(this is not the case for other potential files in the commits of the sample) and no commit is a merge commit.
 
 A `file_commit_chain` scenario looks as follows:
 ```