created readme with description and how-to

README.md

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 license: cc-by-4.0
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-# Dataset for the first Workshop on Information Extraction from Scientific Publications (WIESP)
+# Dataset for the first Workshop on Information Extraction from Scientific Publications (WIESP/2022)
+
+## Dataset Descriptions
+Datasets are in JSON Lines format (each line is a json dictionary).
+The datasets are formatted similarly to the CONLL2003 format in that they associate each token with an NER tag. The tags follow the "B-" and "I-" convention from the IOB2 syntax
+
+Each entry consists of a dictionary with the following keys:
+- `"unique_id"`: a unique identifier for this data sample. Must be included in the predictions.
+- `"tokens"`: the list of tokens (strings) that form the text of this sample. Must be included in the predictions.
+- `"ner_tags"`: the list of NER tags (in IOB2 format)
+
+The following keys are not strictly needed by the participants:
+- `"ner_ids"`: the pre-computed list of ids corresponding ner_tags, as given by the dictionary in ner_tags.json
+- `"label_studio_id"`, `"section"`, `"bibcode"`: references for internal NASA/ADS use.
+
+## How-To
+How to load the data (assuming `./WIESP2022-NER-DEV.jsonl` is in the current directory, change as needed).
+
+How to load into python (as list of dictionaries):
+```
+import json
+with open('./WIESP2022-NER-DEV.jsonl', 'r') as f:
+    wiesp_dev_json = [json.loads(l) for l in list(f)]
+```
+How to load into Huggingface (as a Hugginface Dataset):
+```
+from datasets import Dataset
+wiesp_dev_from_json = Dataset.from_json(path_or_paths='./WIESP2022-NER-DEV.json')
+```