Update README.md

README.md

@@ -42,15 +42,15 @@ At minimum, this metric requires predictions and references as inputs.
 
 ```python
  >>> segmentation_scores = evaluate.load("transformersegmentation/segmentation_scores")
- >>> results = segmentation_scores.compute(references=["w ɛ ɹ ;eword ɪ z ;eword ð ɪ s ;eword", "l ɪ ɾ əl ;eword aɪ z ;eword"], predictions=["w ɛ ɹ ;eword ɪ z ;eword ð ɪ s ;eword", "l ɪ ɾ əl ;eword aɪ z ;eword"])
+ >>> results = segmentation_scores.compute(references=["w ɛ ɹ WORD_BOUNDARY ɪ z WORD_BOUNDARY ð ɪ s WORD_BOUNDARY", "l ɪ ɾ əl WORD_BOUNDARY aɪ z WORD_BOUNDARY"], predictions=["w ɛ ɹ WORD_BOUNDARY ɪ z WORD_BOUNDARY ð ɪ s WORD_BOUNDARY", "l ɪ ɾ əl WORD_BOUNDARY aɪ z WORD_BOUNDARY"])
  >>> print(results)
  {'type_fscore': 1.0, 'type_precision': 1.0, 'type_recall': 1.0, 'token_fscore': 1.0, 'token_precision': 1.0, 'token_recall': 1.0, 'boundary_all_fscore': 1.0, 'boundary_all_precision': 1.0, 'boundary_all_recall': 1.0, 'boundary_noedge_fscore': 1.0, 'boundary_noedge_precision': 1.0, 'boundary_noedge_recall': 1.0}
 
 ```
 
 ### Inputs
-- **predictions** (`list` of `str`): Predicted segmentations, with characters separated with spaces and word boundaries marked with ";eword".
-- **references** (`list` of `str`): Ground truth segmentations, with characters separated with spaces and word boundaries marked with ";eword".
+- **predictions** (`list` of `str`): Predicted segmentations, with characters separated with spaces and word boundaries marked with "WORD_BOUNDARY".
+- **references** (`list` of `str`): Ground truth segmentations, with characters separated with spaces and word boundaries marked with "WORD_BOUNDARY".
 
 ### Output Values