added diagram

README.md

@@ -12,20 +12,19 @@ language:
 size_categories:
 - 10K<n<100K
 ---
+
 # Dataset Card for NL2SH-ALFA
-This dataset is a collection of natural language (English) instructions and corresponding Bash commands.
+This dataset is a collection of natural language (English) instructions and corresponding Bash commands for the task of natural language to Bash translation (NL2SH).
 
 ## Dataset Details
-
 ### Dataset Description
-This dataset contains a test set of 600 manually verified instruction-command pairs, and a training set of 40,939 pairs.
-
-- **Curated by:** ALFA Group at MIT-CSAIL
+This dataset contains a test set of 600 manually verified instruction-command pairs, and a training set of 40,639 unverified pairs for the development and benchmarking of machine translation models. The creation of NL2SH-ALFA was motivated by the need for larger, more accurate NL2SH datasets. The associated [InterCode-ALFA](https://github.com/westenfelder/InterCode-ALFA) benchmark uses the NL2SH-ALFA test set. For more information, please refer to the paper linked below.
+- **Curated by:** Anyscale Learning For All (ALFA) Group at MIT-CSAIL
 - **Language:** English 
 - **License:** MIT License
 
 ### Usage
-Note, the config parameter, NOT the split parameter, selects the train/test data.
+Note, the config parameter, **NOT** the split parameter, selects the train/test data.
 ```bash
 from datasets import load_dataset
 train_dataset = load_dataset("westenfelder/NL2SH-ALFA", "train", split="train")
@@ -33,50 +32,43 @@ test_dataset = load_dataset("westenfelder/NL2SH-ALFA", "test", split="train")
 ```
 
 ### Dataset Sources
-- **Repository:** [GitHub](https://github.com/westenfelder/NL2SH)
-- **Paper:** [Arxiv](https://arxiv.org/abs/2502.06858)
+- **Repository:** [GitHub Repo](https://github.com/westenfelder/NL2SH)
+- **Paper:** [LLM-Supported Natural Language to Bash Translation](https://arxiv.org/abs/2502.06858)
 
 ## Uses
-
-<!-- Address questions around how the dataset is intended to be used. -->
-
 ### Direct Use
-
-<!-- This section describes suitable use cases for the dataset. -->
+This dataset is intended for training and evaluating NL2SH models.
 
 ### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+This dataset is not intended for natural languages other than English, scripting languages or than Bash, nor multi-line Bash scripts.
 
 ## Dataset Structure
-
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+The training set contains two columns:
+- `nl`: string - natural language instruction
+- `bash`: string - Bash command
+The test set contains four columns:
+- `nl`: string - natural language instruction
+- `bash`: string - Bash command
+- `bash2`: string - Bash command (alternative)
+- `difficulty`: int - difficulty level (0, 1, 2) corresponding to (easy, medium, hard)
+Both sets are unordered.
 
 ## Dataset Creation
-
 ### Curation Rationale
-
-<!-- Motivation for the creation of this dataset. -->
+The NL2SH-ALFA dataset was created to increase the amount of NL2SH training data and to address errors in the test sets of previous datasets.
 
 ### Source Data
-
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-
-#### Data Collection and Processing
-
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-
-#### Who are the source data producers?
-
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
+The dataset was produced by combining, deduplicating and filtering multiple datasets from previous work. Additionally, it includes instruction-command pairs scraped from the [tldr-pages](https://github.com/tldr-pages/tldr). Please refer to Section 4.1 of the paper for more information about data collection, processing and filtering.
+![NL2SH-ALFA Dataset Creation](./diagram.png)
 
 ## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+- The number of commands for different utilities is imbalanced, with the most common command being `find`.
+- Since the training set is unverified, there is a risk it contains incorrect instruction-command pairs.
+- This dataset is not intended for multi-line Bash scripts.
 
 ### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+- Users are encouraged to filter or balance the utilities in the dataset according to their use case.
+- Models trained on this dataset may produce incorrect Bash commands, especially for uncommon utilities. Users are encouraged to verify translations.
 
 ## Citation 
 **BibTeX:**