Update README.md

README.md

@@ -51,11 +51,11 @@ task_ids:
 
 - **Homepage:** https://pdi.fbk.eu/pet-dataset/
 - **Paper:** https://arxiv.org/abs/2203.04860
-- **Point of Contact:** pbellan@fbk.eu
+- **Point of Contact:** [Patrizio Bellan] (pbellan@fbk.eu)
 
 ### Dataset Summary
 
-Abstract. Although there is a long tradition of work in NLP on extracting entities and relations from text, to date there exists little work on the acquisition of business processes from unstructured data such as textual corpora of process descriptions. With this work we aim at filling this gap and establishing the first steps towards bridging data-driven information extraction methodologies from Natural Language Processing and the model-based formalization that is aimed from Business Process Management. For this, we develop the first corpus of business process descriptions annotated with activities, gateways, actors and flow information. We present our new resource, including a detailed overview of the annotation schema and guidelines, as well as a variety of baselines to benchmark the difficulty and challenges of business process extraction from text.
+Abstract. Although there is a long tradition of work in NLP on extracting entities and relations from text, to date there exists little work on the acquisition of business processes from unstructured data such as textual corpora of process descriptions. With this work we aim at filling this gap and establishing the first steps towards bridging data-driven information extraction methodologies from Natural Language Processing and the model-based formalization that is aimed from Business Process Management. For this, we develop the first corpus of business process descriptions annotated with activities, actors, activity data, gateways and their conditions. We present our new resource to benchmark the difficulty and challenges of business process extraction from text.
 
 ### Supported Tasks and Leaderboards
 
@@ -67,36 +67,44 @@ English
 
 ## Dataset Structure
 
-Test set to beanchmark 'Process Extraction from Text' approaches.
+Test set to beanchmark *Business Process Extraction from Text* approaches.
 
 ### Data Instances
 
-[More Information Needed]
+For each instance, there is a document name representing the name of the document of the Friedrich *et al.* dataset, an integer representing the number of the sentence, a list of tokens representing the words of the sentence instance, and a list of *ner tags* (in IOB2 format) representing the annotation of process elements of the sentence.
+
+```
+{
+  "document name":"doc-1.1",
+  "sentence-ID":1,
+  "tokens":["Whenever","the","sales","department","receives","an","order",",","a","new","process","instance","is","created","."],
+  "ner-tags":["O","B-Actor","I-Actor","I-Actor","B-Activity","B-Activity Data","I-Activity Data","O","O","O","O","O","O","O","O"]
+}
+```
 
 ### Data Fields
 
-'document name'
-
-'sentence-ID'
-
-'tokens'
-
-'ner-tags': 
-  "O",
-  "B-Actor",
-  "I-Actor",
-  "B-Activity",
-  "I-Activity",
-  "B-Activity Data",
-  "I-Activity Data",
-  "B-Further Specification",
-  "I-Further Specification",
-  "B-XOR Gateway",
-  "I-XOR Gateway",
-  "B-Condition Specification",
-  "I-Condition Specification",
-  "B-AND Gateway",
-  "I-AND Gateway",
+- *document name*: a string used to represent the name of the document.
+- *sentence-ID*: an integer (starting from 0) representing the number of the sentence within the document.
+- *tokens*: a list of string representing the words of the sentence
+- *ner-tags*: a list of string representing the annotation for each word.
+
+The allowed **ner-tags** are: 
+  - "O": 
+  - "B-Actor",
+  - "I-Actor",
+  - "B-Activity",
+  - "I-Activity",
+  - "B-Activity Data",
+  - "I-Activity Data",
+  - "B-Further Specification",
+  - "I-Further Specification",
+  - "B-XOR Gateway",
+  - "I-XOR Gateway",
+  - "B-Condition Specification",
+  - "I-Condition Specification",
+  - "B-AND Gateway",
+  - "I-AND Gateway",
 
 ### Data Splits
 
@@ -159,8 +167,11 @@ Expert Annotators
 
 ### Dataset Curators
 
-Patrizio Bellan, Mauro Dragoni, Chiara Ghidini, Han van der Aa, Simone Ponzetto
-[More Information Needed]
+- Patrizio Bellan (
+- Mauro Dragoni
+- Chiara Ghidini
+- Han van der Aa
+- Simone Ponzetto
 
 ### Licensing Information