Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
Turkish
Size:
100K<n<1M
License:
Commit
·
e012022
1
Parent(s):
19c2f04
Replace YAML keys from int to str
Browse filesReplace YAML metadata integer keys with strings, as the Hub does not support integers.
See: https://github.com/huggingface/datasets/issues/5275
README.md
CHANGED
@@ -17,7 +17,6 @@ task_categories:
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- token-classification
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task_ids:
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- named-entity-recognition
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-
paperswithcode_id: null
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pretty_name: TurkishShrinkedNer
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dataset_info:
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features:
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@@ -29,103 +28,103 @@ dataset_info:
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sequence:
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class_label:
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names:
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0: O
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1: B-academic
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2: I-academic
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3: B-academic_person
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4: I-academic_person
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5: B-aircraft
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6: I-aircraft
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7: B-album_person
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8: I-album_person
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9: B-anatomy
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10: I-anatomy
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11: B-animal
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12: I-animal
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13: B-architect_person
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14: I-architect_person
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15: B-capital
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16: I-capital
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17: B-chemical
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18: I-chemical
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19: B-clothes
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20: I-clothes
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21: B-country
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22: I-country
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-
23: B-culture
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24: I-culture
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25: B-currency
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26: I-currency
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27: B-date
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28: I-date
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29: B-food
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30: I-food
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31: B-genre
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32: I-genre
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33: B-government
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66 |
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34: I-government
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35: B-government_person
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36: I-government_person
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37: B-language
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38: I-language
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39: B-location
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40: I-location
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41: B-material
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42: I-material
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43: B-measure
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44: I-measure
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45: B-medical
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46: I-medical
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47: B-military
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48: I-military
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49: B-military_person
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50: I-military_person
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51: B-nation
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52: I-nation
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53: B-newspaper
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86 |
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54: I-newspaper
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55: B-organization
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56: I-organization
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57: B-organization_person
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58: I-organization_person
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59: B-person
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60: I-person
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61: B-production_art_music
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62: I-production_art_music
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63: B-production_art_music_person
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64: I-production_art_music_person
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65: B-quantity
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-
66: I-quantity
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67: B-religion
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68: I-religion
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69: B-science
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70: I-science
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71: B-shape
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-
72: I-shape
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-
73: B-ship
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106 |
-
74: I-ship
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-
75: B-software
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108 |
-
76: I-software
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77: B-space
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-
78: I-space
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-
79: B-space_person
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-
80: I-space_person
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81: B-sport
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82: I-sport
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83: B-sport_name
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84: I-sport_name
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85: B-sport_person
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-
86: I-sport_person
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87: B-structure
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88: I-structure
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89: B-subject
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90: I-subject
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91: B-tech
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92: I-tech
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93: B-train
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94: I-train
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95: B-vehicle
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-
96: I-vehicle
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splits:
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- name: train
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num_bytes: 200728389
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|
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- token-classification
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task_ids:
|
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- named-entity-recognition
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|
|
20 |
pretty_name: TurkishShrinkedNer
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21 |
dataset_info:
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22 |
features:
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|
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sequence:
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29 |
class_label:
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30 |
names:
|
31 |
+
'0': O
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32 |
+
'1': B-academic
|
33 |
+
'2': I-academic
|
34 |
+
'3': B-academic_person
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35 |
+
'4': I-academic_person
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36 |
+
'5': B-aircraft
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37 |
+
'6': I-aircraft
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38 |
+
'7': B-album_person
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39 |
+
'8': I-album_person
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40 |
+
'9': B-anatomy
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41 |
+
'10': I-anatomy
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42 |
+
'11': B-animal
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43 |
+
'12': I-animal
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44 |
+
'13': B-architect_person
|
45 |
+
'14': I-architect_person
|
46 |
+
'15': B-capital
|
47 |
+
'16': I-capital
|
48 |
+
'17': B-chemical
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49 |
+
'18': I-chemical
|
50 |
+
'19': B-clothes
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51 |
+
'20': I-clothes
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52 |
+
'21': B-country
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53 |
+
'22': I-country
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54 |
+
'23': B-culture
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55 |
+
'24': I-culture
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56 |
+
'25': B-currency
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57 |
+
'26': I-currency
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58 |
+
'27': B-date
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59 |
+
'28': I-date
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60 |
+
'29': B-food
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61 |
+
'30': I-food
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62 |
+
'31': B-genre
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63 |
+
'32': I-genre
|
64 |
+
'33': B-government
|
65 |
+
'34': I-government
|
66 |
+
'35': B-government_person
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67 |
+
'36': I-government_person
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68 |
+
'37': B-language
|
69 |
+
'38': I-language
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70 |
+
'39': B-location
|
71 |
+
'40': I-location
|
72 |
+
'41': B-material
|
73 |
+
'42': I-material
|
74 |
+
'43': B-measure
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75 |
+
'44': I-measure
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76 |
+
'45': B-medical
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77 |
+
'46': I-medical
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78 |
+
'47': B-military
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79 |
+
'48': I-military
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80 |
+
'49': B-military_person
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81 |
+
'50': I-military_person
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82 |
+
'51': B-nation
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83 |
+
'52': I-nation
|
84 |
+
'53': B-newspaper
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85 |
+
'54': I-newspaper
|
86 |
+
'55': B-organization
|
87 |
+
'56': I-organization
|
88 |
+
'57': B-organization_person
|
89 |
+
'58': I-organization_person
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90 |
+
'59': B-person
|
91 |
+
'60': I-person
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92 |
+
'61': B-production_art_music
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93 |
+
'62': I-production_art_music
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94 |
+
'63': B-production_art_music_person
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95 |
+
'64': I-production_art_music_person
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96 |
+
'65': B-quantity
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97 |
+
'66': I-quantity
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+
'67': B-religion
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99 |
+
'68': I-religion
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100 |
+
'69': B-science
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101 |
+
'70': I-science
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102 |
+
'71': B-shape
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103 |
+
'72': I-shape
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104 |
+
'73': B-ship
|
105 |
+
'74': I-ship
|
106 |
+
'75': B-software
|
107 |
+
'76': I-software
|
108 |
+
'77': B-space
|
109 |
+
'78': I-space
|
110 |
+
'79': B-space_person
|
111 |
+
'80': I-space_person
|
112 |
+
'81': B-sport
|
113 |
+
'82': I-sport
|
114 |
+
'83': B-sport_name
|
115 |
+
'84': I-sport_name
|
116 |
+
'85': B-sport_person
|
117 |
+
'86': I-sport_person
|
118 |
+
'87': B-structure
|
119 |
+
'88': I-structure
|
120 |
+
'89': B-subject
|
121 |
+
'90': I-subject
|
122 |
+
'91': B-tech
|
123 |
+
'92': I-tech
|
124 |
+
'93': B-train
|
125 |
+
'94': I-train
|
126 |
+
'95': B-vehicle
|
127 |
+
'96': I-vehicle
|
128 |
splits:
|
129 |
- name: train
|
130 |
num_bytes: 200728389
|