Update README.md

README.md

@@ -59,14 +59,6 @@ task_ids:
 
 EpiSet4NER-v2 is a gold-standard dataset for epidemiological entity recognition of location, epidemiologic types (e.g. "prevalence", "annual incidence", "estimated occurrence"), and epidemiological rates (e.g. "1.7 per 1,000,000 live births", "2.1:1.000.000", "one in five million", "0.03%") created by the [Genetic and Rare Diseases Information Center (GARD)](https://rarediseases.info.nih.gov/), a program in [the National Center for Advancing Translational Sciences](https://ncats.nih.gov/), one of the 27 [National Institutes of Health](https://www.nih.gov/). It was labeled programmatically using spaCy NER and rule-based methods, then manually validated by biomedical researchers, including a GARD curator (genetic and rare disease expert). This weakly-supervised teaching method allowed us to construct this high quality dataset in an efficient manner and achieve satisfactory performance on a multi-type token classification problem. It was used to train [EpiExtract4GARD-v2](https://huggingface.co/ncats/EpiExtract4GARD-v2), a BioBERT-based model fine-tuned for NER.
 
-An [example](https://pubmed.ncbi.nlm.nih.gov/24237863/) of 'train' looks as follows.
-```
-{
-    "id": "333",
-    "tokens": ['Conclusions', 'The', 'birth', 'prevalence', 'of', 'CLD', 'in', 'the', 'northern', 'Netherlands', 'was', '21.1/10,000', 'births', '.'],
-    "ner_tags":  [0, 0, 0, 3, 0, 0, 0, 0, 0, 1, 0, 5, 6, 0],
-}
-```
 ### Data Fields
 
 The data fields are the same among all splits.