further suppress WordNet warnings

.ipynb_checkpoints/chinesemeteor-checkpoint.py

@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """
-METEOR (Chinese) — with Jieba pre-segmentation + Real CwnGraph Chinese WordNet
+Chinese METEOR — with Jieba pre-segmentation + CwnGraph Chinese WordNet
 """
 import jieba_fast as jieba
 import datasets
@@ -25,6 +25,10 @@ import nltk
 import evaluate
 import re
 
+# suppress WordNet warnings
+import warnings
+warnings.filterwarnings("ignore")
+
 # Download once
 nltk.download("wordnet", quiet=True)
 nltk.download("omw-1.4", quiet=True)
@@ -87,7 +91,7 @@ Examples:
     to use the function.
 
     >>> cmeteor = evaluate.load("raptorkwok/chinesemeteor")
-    >>> results = cmeteor.compute(references=["Reference Sentence in Chinese"], predictions=["Predicted Sentence in Chinese"])
+    >>> results = cmeteor.compute(references=["我在這裡吃飯"], predictions=["我在這兒吃晚飯"])
     >>> print(results)
     {'meteor': 0.5111111111111111, 'scores': [0.5111111111111111]}
 """

chinesemeteor.py

@@ -13,7 +13,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """
-METEOR (Chinese) — with Jieba pre-segmentation + Real CwnGraph Chinese WordNet
+Chinese METEOR — with Jieba pre-segmentation + CwnGraph Chinese WordNet
 """
 import jieba_fast as jieba
 import datasets
@@ -25,6 +25,10 @@ import nltk
 import evaluate
 import re
 
+# suppress WordNet warnings
+import warnings
+warnings.filterwarnings("ignore")
+
 # Download once
 nltk.download("wordnet", quiet=True)
 nltk.download("omw-1.4", quiet=True)
@@ -87,7 +91,7 @@ Examples:
     to use the function.
 
     >>> cmeteor = evaluate.load("raptorkwok/chinesemeteor")
-    >>> results = cmeteor.compute(references=["Reference Sentence in Chinese"], predictions=["Predicted Sentence in Chinese"])
+    >>> results = cmeteor.compute(references=["我在這裡吃飯"], predictions=["我在這兒吃晚飯"])
     >>> print(results)
     {'meteor': 0.5111111111111111, 'scores': [0.5111111111111111]}
 """