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@@ -30,7 +30,7 @@ dataset_info:
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  sampling_rate: 16000
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  - name: sentence
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  dtype: string
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- - name: entities
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  sequence:
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  class_label:
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  names:
@@ -139,21 +139,62 @@ dataset_info:
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  '102': I-corporation
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  '103': I-time
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  '104': O
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  splits:
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  - name: de
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- num_bytes: 1103674014.714
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  num_examples: 1966
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  - name: fr
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- num_bytes: 1053785539.44
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  num_examples: 1656
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  - name: nl
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- num_bytes: 600220358.88
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  num_examples: 1120
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  - name: es
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- num_bytes: 1151943335.024
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  num_examples: 1512
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- download_size: 3330795263
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- dataset_size: 3909623248.0580006
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  ---
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  # Dataset Card for "spoken-ner"
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  sampling_rate: 16000
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  - name: sentence
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  dtype: string
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+ - name: unified_entities
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  sequence:
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  class_label:
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  names:
 
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  '102': I-corporation
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  '103': I-time
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  '104': O
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+ - name: ontonotes_entities
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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-cardinal number
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+ '2': B-date
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+ '3': I-date
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+ '4': B-person
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+ '5': I-person
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+ '6': B-group
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+ '7': B-geopolitical area
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+ '8': I-geopolitical area
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+ '9': B-law
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+ '10': I-law
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+ '11': B-organization
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+ '12': I-organization
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+ '13': B-percent
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+ '14': I-percent
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+ '15': B-ordinal number
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+ '16': B-money
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+ '17': I-money
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+ '18': B-work of art
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+ '19': I-work of art
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+ '20': B-facility
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+ '21': B-time
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+ '22': I-cardinal number
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+ '23': B-location
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+ '24': B-quantity
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+ '25': I-quantity
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+ '26': I-group
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+ '27': I-location
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+ '28': B-product
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+ '29': I-time
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+ '30': B-event
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+ '31': I-event
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+ '32': I-facility
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+ '33': B-language
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+ '34': I-product
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+ '35': I-ordinal number
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+ '36': I-language
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  splits:
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  - name: de
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+ num_bytes: 1104049942.714
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  num_examples: 1966
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  - name: fr
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+ num_bytes: 1054225315.44
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  num_examples: 1656
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  - name: nl
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+ num_bytes: 600447374.88
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  num_examples: 1120
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  - name: es
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+ num_bytes: 1152365703.024
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  num_examples: 1512
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+ download_size: 3330860792
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+ dataset_size: 3911088336.0580006
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  ---
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  # Dataset Card for "spoken-ner"
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