init

README.md

@@ -22,14 +22,13 @@ pretty_name: BioNLP2004
 - **Paper:** [https://aclanthology.org/U15-1010.pdf](https://aclanthology.org/U15-1010.pdf)
 - **Dataset:** BioNLP2004
 - **Domain:** Biochemical
-- **Number of Entity:** 4
+- **Number of Entity:** 5
 
 ### Dataset Summary
 BioNLP2004 NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project.
-Original BioNLP2004 dataset contains training and test.
-We take a half amount of test instances randomly from the training set and create a validation set with it.
+BioNLP2004 dataset contains training and test only, so we randomly sample a half size of test instances from the training set to create validation set. 
 
-- Entity Types:`ORG`, `LOC`, `PER`, `MISC`
+- Entity Types: `DNA`, `protein`, `cell_type`, `cell_line`, `RNA`
 
 ## Dataset Structure
 
@@ -38,8 +37,8 @@ An example of `train` looks as follows.
 
 ```
 {
-    "tags": [0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-    "tokens": ["1", ".", "1", ".", "4", "Borrower", "engages", "in", "criminal", "conduct", "or", "is", "involved", "in", "criminal", "activities", ";"]
+    'tags': [0, 0, 0, 0, 3, 0, 9, 10, 0, 0, 0, 0, 0, 7, 8, 0, 3, 0, 0, 9, 10, 10, 0, 0],
+    'tokens': ['In', 'the', 'presence', 'of', 'Epo', ',', 'c-myb', 'mRNA', 'declined', 'and', '20', '%', 'of', 'K562', 'cells', 'synthesized', 'Hb', 'regardless', 'of', 'antisense', 'myb', 'RNA', 'expression', '.']
 }
 ```
 
@@ -48,10 +47,16 @@ The label2id dictionary can be found at [here](https://huggingface.co/datasets/t
 ```python
 {
     "O": 0,
-    "I-ORG": 1,
-    "I-LOC": 2,
-    "I-PER": 3,
-    "I-MISC": 4
+    "B-DNA": 1,
+    "I-DNA": 2,
+    "B-protein": 3,
+    "I-protein": 4,
+    "B-cell_type": 5,
+    "I-cell_type": 6,
+    "B-cell_line": 7,
+    "I-cell_line": 8,
+    "B-RNA": 9,
+    "I-RNA": 10
 }
 ```
 
@@ -59,7 +64,7 @@ The label2id dictionary can be found at [here](https://huggingface.co/datasets/t
 
 |  name   |train|validation|test|
 |---------|----:|---------:|---:|
-|fin      |861  |       303| 303|
+|fin      |16619  |       1927| 3856|
 
 ### Citation Information