docs: update name

README.md

@@ -58,21 +58,12 @@ configs:
   data_files:
   - split: queries
     path: data/queries.jsonl
-pretty_name: SCALR (MTEB format)
+pretty_name: SCALR (MLEB version)
 ---
-# SCALR (MTEB format)
-This is the [SCALR](https://github.com/lexeme-dev/scalr) evaluation dataset formatted in the [Massive Text Embedding Benchmark (MTEB)](https://github.com/embeddings-benchmark/mteb) information retrieval dataset format.
+# SCALR (MLEB version)
+This is the version of the [SCALR](https://github.com/lexeme-dev/scalr) evaluation dataset used in the Massive Legal Embedding Benchmark (MLEB) by [Isaacus](https://isaacus.com/).
 
-This dataset is intended to facilitate the consistent and reproducible evaluation of information retrieval models on SCALR with the [`mteb`](https://github.com/embeddings-benchmark/mteb) embedding model evaluation framework.
-
-More specifically, this dataset tests the ability of information retrieval models to retrieve relevant legal holdings to complex, reasoning-intensive legal questions.
-
-This dataset has been processed into the MTEB format by [Isaacus](https://isaacus.com/), a legal AI research company.
-
-## Methodology 🧪
-To understand how SCALR itself was created, refer to its [documentation](https://github.com/lexeme-dev/scalr).
-
-This dataset was formatted by taking the test split of SCALR, splitting it in half (after random shuffling) (to allow for the remainder of the dataset to be used for validation), and treating questions as anchors and correct holdings as positive passages, and adding incorrect holdings to the global passage corpus.
+This dataset tests the ability of information retrieval models to retrieve relevant legal holdings to complex, reasoning-intensive legal questions.
 
 ## Structure 🗂️
 As per the MTEB information retrieval dataset format, this dataset comprises three splits, `default`, `corpus` and `queries`.
@@ -83,6 +74,11 @@ The `corpus` split contains holdings, with the text of a holding being stored in
 
 The `queries` split contains questions, with the text of a question being stored in the `text` key and its id being stored in the `_id` key.
 
+## Methodology 🧪
+To understand how SCALR itself was created, refer to its [documentation](https://github.com/lexeme-dev/scalr).
+
+This dataset was formatted by taking the test split of SCALR, splitting it in half (after random shuffling) (to allow for the remainder of the dataset to be used for validation), and treating questions as anchors and correct holdings as positive passages, and adding incorrect holdings to the global passage corpus.
+
 ## License 📜
 This dataset is licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).