Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
100K - 1M
ArXiv:
License:
Update README.md
Browse files
README.md
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@@ -31,6 +31,29 @@ A Dataset and Analysis on Short-Term Temporal Shifts, AACL main conference 2022"
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a timestamp which distributes from September 2019 to August 2021.
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- Entity Types: `corperation`, `creative_work`, `event`, `group`, `location`, `product`, `person`
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## Dataset Structure
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### Data Instances
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a timestamp which distributes from September 2019 to August 2021.
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- Entity Types: `corperation`, `creative_work`, `event`, `group`, `location`, `product`, `person`
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***PREPROCESSING:***
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We pre-process tweets before the annotation to normalize some artifacts, converting URLs into a special token `{{URL}}` and non-verified usernames into `{{USERNAME}}`.
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For verified usernames, we replace its display name with symbols `{@}`.
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For example, a tweet
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```
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Get the all-analog Classic Vinyl Edition
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of "Takin' Off" Album from @herbiehancock
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via @bluenoterecords link below:
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http://bluenote.lnk.to/AlbumOfTheWeek
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```
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is transformed into the following text.
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```
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Get the all-analog Classic Vinyl Edition
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of "Takin' Off" Album from {@Herbie Hancock@}
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via {{USERNAME}} link below: {{URL}}
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```
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We ask annotators to ignore those special tokens but label the verified users' mentions.
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## Dataset Structure
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### Data Instances
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