Update README.md

README.md

@@ -4,7 +4,72 @@ task_categories:
 - question-answering
 language:
 - en
-pretty_name: Causal Business Processes Reasoning Benchmark
+tags:
+- Business Process Management
+- Causal
+- NLP
+- Reasoning
+pretty_name: BP^C
 size_categories:
-- n=3077
----
+- 1K<n<10K
+---
+# BP<sup>C</sup>: A Benchmark Dataset for Causal Business Process Reasoning
+
+# Dataset Card for BP<sup>C</sup>
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks](#supported-tasks)
+  - [Languages](#languages)
+<!--- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+- [Annotation Guidelines](#annotationguidelines)
+- [Update](#updates)
+- [Loading data](#loadingdata)-->
+
+## Dataset Description
+
+- **Homepage:** https://huggingface.co/datasets/ibm/BPC
+- **Paper:** https://arxiv.org/abs/2406.05506
+- **Point of Contact:** <!--[Patrizio Bellan](pbellan@fbk.eu)-->
+- **Version:** 1.0
+
+### Dataset Summary
+
+Abstract. Large Language Models (LLMs) are increasingly used for boosting organizational efficiency and automating tasks. 
+While not originally designed for complex cognitive processes, recent efforts have further extended to employ LLMs in activities such as reasoning, planning, 
+and decision-making. In business processes, such abilities could be invaluable for leveraging on the massive corpora LLMs have been trained on for gaining a deep understanding 
+of such processes. In adherence to this goal, we attach here the BP<sup>C</sup> dataset, a newly developed set of process-aware Q&A that can be used to assess 
+the ability of LLMs to reason about causal and process perspectives of business operations. 
+We refer to this view as Causally-augmented Business Processes (BP^C). The benchmark comprises a set of domain-specific BP<sup>C</sup> related situations, 
+a set of questions about these situations, and a set of ground truth answers to these questions. 
+Reasoning on BP^C is of crucial importance for process interventions and process improvement. 
+The benchmark could be used in one of two possible modalities: testing the performance of any target LLM and training an LLM to advance its capability to reason about BP^C.
+
+### Supported Tasks
+
+- Question Answering
+- Causal and Process Reasoning
+- LLM tunning and testing
+
+### Languages
+
+- English