added file list

README.md

@@ -5,7 +5,7 @@ license: cc-by-4.0
 
 ## Dataset Description
 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
+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.
@@ -35,4 +35,15 @@ with open("./WIESP2022-NER-DEV.jsonl", 'r') as f:
 ```
 from datasets import Dataset
 wiesp_dev_from_json = Dataset.from_json(path_or_paths="./WIESP2022-NER-DEV.jsonl")
+```
+
+## File list
+```
+├── WIESP2022-NER-TRAINING.jsonl : 1753 samples for training.
+├── WIESP2022-NER-DEV.jsonl : 20 samples for development.
+├── WIESP2022-NER-VALIDATION-NO-LABELS.jsonl : 1366 samples for validation without the NER labels. Used for the WIESP2022 workshop.
+├── README.MD: this file.
+└── scoring-scripts/ : scripts used to evaluate submissions.
+    ├── compute_MCC.py : computes the Matthews correlation coefficient between two datasets.
+    └── compute_seqeval.py : computes the seqeval scores (precision, recall, f1 overall and for each class) between two datasets.
 ```