README.md not readme.md

readme.md → README.md

@@ -1,6 +1,20 @@
 # Wiki Entity Similarity
 
-This dataset is generated by aggregating the link text that refers to various articles in context. For instance, if wiki article A refers to article B as C, then C is added to the list of aliases for article B, and the pair (B, C) is included in the dataset.
+Usage:
+``py`
+from datasets import load_dataset
+
+corpus = load_dataset('Exr0n/wiki-entity-similarity', '2018thresh20corpus', split='train')
+assert corpus[0] == {'article': 'A1000 road', 'link_text': 'A1000', 'is_same': 1}
+
+pairs = load_dataset('Exr0n/wiki-entity-similarity', '2018thresh20pairs', split='train')
+assert corpus[0] == {'article': 'Rhinobatos', 'link_text': 'Ehinobatos beurleni', 'is_same': 1}
+assert len(corpus) == 4_793_180
+```
+
+## Corpus (`name=*corpus`)
+
+The corpora in this are generated by aggregating the link text that refers to various articles in context. For instance, if wiki article A refers to article B as C, then C is added to the list of aliases for article B, and the pair (B, C) is included in the dataset.
 
 Following (DPR https://arxiv.org/pdf/2004.04906.pdf), we use the English Wikipedia dump from Dec. 20, 2018 as the source documents for link collection. 
 
@@ -12,4 +26,12 @@ The dataset includes three quality levels, distinguished by the minimum number o
 | 10 | 605,775 | 4,407,409 |
 | 20 | 324,949 | 3,195,545 |
 
+## Training Pairs (`name=*pairs`)
+This dataset also includes training pair datasets (with both positive and negative examples) intended for training classifiers. The train/dev/test split is 75/15/10 % of each corpus. 
+
+### Training Data Generation
+The training pairs in this dataset are generated by taking each example from the corpus as a positive example, and creating a new negative example from the article title of the positive example and a random link text from a different article.
+
+The articles featured in each split are disjoint from the other splits, and each split has the same number of positive (semantically the same) and negative (semantically different) examples.
+
 Generation scripts can be found [in the GitHub repo](https://github.com/Exr0nProjects/wiki-entity-similarity).