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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@@ -50,6 +50,29 @@ 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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via {{USERNAME}} link below: {{URL}}
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```
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A simple function to format tweet follows below.
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```python
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import re
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from urlextract import URLExtract
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extractor = URLExtract()
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def format_tweet(tweet):
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# mask web urls
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urls = extractor.find_urls(tweet)
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for url in urls:
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tweet = tweet.replace(url, "{{URL}}")
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# format twitter account
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tweet = re.sub(r"\b(\s*)(@[\S]+)\b", r'\1{\2@}', tweet)
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return tweet
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target = tweet = """Get the all-analog Classic Vinyl Edition of "Takin' Off" Album from @herbiehancock via @bluenoterecords link below: http://bluenote.lnk.to/AlbumOfTheWeek"""
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target_format = format_tweet(target)
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print(target_format)
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'Get the all-analog Classic Vinyl Edition of "Takin\' Off" Album from {@herbiehancock@} via {@bluenoterecords@} 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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