Replace YAML keys from int to str (#1)

- Replace YAML keys from int to str (e0120224d62c3427abdea09977a7da83b030b0ae)

README.md

@@ -17,7 +17,6 @@ task_categories:
 - token-classification
 task_ids:
 - named-entity-recognition
-paperswithcode_id: null
 pretty_name: TurkishShrinkedNer
 dataset_info:
   features:
@@ -29,103 +28,103 @@ dataset_info:
     sequence:
       class_label:
         names:
-          0: O
-          1: B-academic
-          2: I-academic
-          3: B-academic_person
-          4: I-academic_person
-          5: B-aircraft
-          6: I-aircraft
-          7: B-album_person
-          8: I-album_person
-          9: B-anatomy
-          10: I-anatomy
-          11: B-animal
-          12: I-animal
-          13: B-architect_person
-          14: I-architect_person
-          15: B-capital
-          16: I-capital
-          17: B-chemical
-          18: I-chemical
-          19: B-clothes
-          20: I-clothes
-          21: B-country
-          22: I-country
-          23: B-culture
-          24: I-culture
-          25: B-currency
-          26: I-currency
-          27: B-date
-          28: I-date
-          29: B-food
-          30: I-food
-          31: B-genre
-          32: I-genre
-          33: B-government
-          34: I-government
-          35: B-government_person
-          36: I-government_person
-          37: B-language
-          38: I-language
-          39: B-location
-          40: I-location
-          41: B-material
-          42: I-material
-          43: B-measure
-          44: I-measure
-          45: B-medical
-          46: I-medical
-          47: B-military
-          48: I-military
-          49: B-military_person
-          50: I-military_person
-          51: B-nation
-          52: I-nation
-          53: B-newspaper
-          54: I-newspaper
-          55: B-organization
-          56: I-organization
-          57: B-organization_person
-          58: I-organization_person
-          59: B-person
-          60: I-person
-          61: B-production_art_music
-          62: I-production_art_music
-          63: B-production_art_music_person
-          64: I-production_art_music_person
-          65: B-quantity
-          66: I-quantity
-          67: B-religion
-          68: I-religion
-          69: B-science
-          70: I-science
-          71: B-shape
-          72: I-shape
-          73: B-ship
-          74: I-ship
-          75: B-software
-          76: I-software
-          77: B-space
-          78: I-space
-          79: B-space_person
-          80: I-space_person
-          81: B-sport
-          82: I-sport
-          83: B-sport_name
-          84: I-sport_name
-          85: B-sport_person
-          86: I-sport_person
-          87: B-structure
-          88: I-structure
-          89: B-subject
-          90: I-subject
-          91: B-tech
-          92: I-tech
-          93: B-train
-          94: I-train
-          95: B-vehicle
-          96: I-vehicle
+          '0': O
+          '1': B-academic
+          '2': I-academic
+          '3': B-academic_person
+          '4': I-academic_person
+          '5': B-aircraft
+          '6': I-aircraft
+          '7': B-album_person
+          '8': I-album_person
+          '9': B-anatomy
+          '10': I-anatomy
+          '11': B-animal
+          '12': I-animal
+          '13': B-architect_person
+          '14': I-architect_person
+          '15': B-capital
+          '16': I-capital
+          '17': B-chemical
+          '18': I-chemical
+          '19': B-clothes
+          '20': I-clothes
+          '21': B-country
+          '22': I-country
+          '23': B-culture
+          '24': I-culture
+          '25': B-currency
+          '26': I-currency
+          '27': B-date
+          '28': I-date
+          '29': B-food
+          '30': I-food
+          '31': B-genre
+          '32': I-genre
+          '33': B-government
+          '34': I-government
+          '35': B-government_person
+          '36': I-government_person
+          '37': B-language
+          '38': I-language
+          '39': B-location
+          '40': I-location
+          '41': B-material
+          '42': I-material
+          '43': B-measure
+          '44': I-measure
+          '45': B-medical
+          '46': I-medical
+          '47': B-military
+          '48': I-military
+          '49': B-military_person
+          '50': I-military_person
+          '51': B-nation
+          '52': I-nation
+          '53': B-newspaper
+          '54': I-newspaper
+          '55': B-organization
+          '56': I-organization
+          '57': B-organization_person
+          '58': I-organization_person
+          '59': B-person
+          '60': I-person
+          '61': B-production_art_music
+          '62': I-production_art_music
+          '63': B-production_art_music_person
+          '64': I-production_art_music_person
+          '65': B-quantity
+          '66': I-quantity
+          '67': B-religion
+          '68': I-religion
+          '69': B-science
+          '70': I-science
+          '71': B-shape
+          '72': I-shape
+          '73': B-ship
+          '74': I-ship
+          '75': B-software
+          '76': I-software
+          '77': B-space
+          '78': I-space
+          '79': B-space_person
+          '80': I-space_person
+          '81': B-sport
+          '82': I-sport
+          '83': B-sport_name
+          '84': I-sport_name
+          '85': B-sport_person
+          '86': I-sport_person
+          '87': B-structure
+          '88': I-structure
+          '89': B-subject
+          '90': I-subject
+          '91': B-tech
+          '92': I-tech
+          '93': B-train
+          '94': I-train
+          '95': B-vehicle
+          '96': I-vehicle
   splits:
   - name: train
     num_bytes: 200728389