add explicit docs on the features using an example

README.md

@@ -87,11 +87,6 @@ fine-tune existing models or build new ones.
    compressed artifact is downloaded and extracted by the Hugging Face
    datasets library to yield the examples in the dataset.
 
-## Features
-The FIBO dataset is composed of triples representing the relationships
-between different financial concepts and named individuals such as
-market participants, corporations, and contractual agents. 
-
 ### Usage
 First make sure you have the requirements installed:
 
@@ -107,11 +102,44 @@ from datasets import load_dataset
 dataset = load_dataset('wikipunk/fibo2023Q3', split='train')
 ```
 
+## Features
+The FIBO dataset is composed of triples representing the relationships
+between different financial concepts and named individuals such as
+market participants, corporations, and contractual agents. 
+
 #### Note on Format:
 The subject, predicate, and object features are stored in N3 notation
 with no prefix mappings. This allows users to parse each component
 using `rdflib.util.from_n3` from the RDFLib Python library.
 
+### 1. **Subject** (`string`)
+The subject of a triple is the primary entity or focus of the statement. In this dataset, the subject often represents a specific financial instrument or entity. For instance:
+`<https://spec.edmcouncil.org/fibo/ontology/SEC/Equities/EquitiesExampleIndividuals/XNYSListedTheCoca-ColaCompanyCommonStock>`
+refers to the common stock of The Coca-Cola Company that is listed on
+the NYSE.
+
+### 2. **Predicate** (`string`)
+The predicate of a triple indicates the nature of the relationship between the subject and the object. It describes a specific property, characteristic, or connection of the subject. In our example:
+`<https://spec.edmcouncil.org/fibo/ontology/SEC/Securities/SecuritiesListings/isTradedOn>`
+signifies that the financial instrument (subject) is traded on a
+particular exchange (object).
+
+### 3. **Object** (`string`)
+The object of a triple is the entity or value that is associated with the subject via the predicate. It can be another financial concept, a trading platform, or any other related entity. In the context of our example:
+`<https://spec.edmcouncil.org/fibo/ontology/FBC/FunctionalEntities/NorthAmericanEntities/USMarketsAndExchangesIndividuals/NewYorkStockExchange>`
+represents the New York Stock Exchange where the aforementioned
+Coca-Cola common stock is traded.
+
+#### Note:
+The dataset contains example individuals from the ontology as
+reference points. These examples provide a structured framework for
+understanding the relationships and entities within the financial
+domain. However, the individuals included are not exhaustive. With
+advancements in Large Language Models, especially Retrieval Augmented
+Generation (RAG), there's potential to generate and expand upon these
+examples, enriching the dataset with more structured data and
+insights.
+
 ### Example
 Here is an example of a triple in the dataset:
 - Subject: `"<https://spec.edmcouncil.org/fibo/ontology/FBC/FunctionalEntities/MarketsIndividuals/ServiceProvider-L-JEUVK5RWVJEN8W0C9M24>"`