Cybersecurity NER corpus 2019
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The cybersecurity NER corpus 2019 contains two corpora:soft_flaw - 1000 binary annotated tweets (TRUE: tweet mentions a software/system/device related security issue (vulnerability, exploit, patch), a malware, or a hacking method; FALSE: otherwise)class distribution: TRUE - 283, FALSE - 717soft_flaw_NER - ca. 1000 NER annotations marking the name of the software/system/device/company with a security related issue, or the name of a malwareThe same tweet might be included in both corpora, however the vast majority of tweets is different across two corpora.Files are in the jsonl format' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["corpus","cybersecurity","NER"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The cybersecurity NER corpus 2019 contains two corpora:soft_flaw - 1000 binary annotated tweets (TRUE: tweet mentions a software/system/device related security issue (vulnerability, exploit, patch), a malware, or a hacking method; FALSE: otherwise)class distribution: TRUE - 283, FALSE - 717soft_flaw_NER - ca. 1000 NER annotations marking the name of the software/system/device/company with a security related issue, or the name of a malwareThe same tweet might be included in both corpora, however the vast majority of tweets is different across two corpora.Files are in the jsonl format' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The cybersecurity NER corpus 2019 contains two corpora:soft_flaw - 1000 binary annotated tweets (TRUE: tweet mentions a software/system/device related security issue (vulnerability, exploit, patch), a malware, or a hacking method; FALSE: otherwise)class distribution: TRUE - 283, FALSE - 717soft_flaw_NER - ca. 1000 NER annotations marking the name of the software/system/device/company with a security related issue, or the name of a malwareThe same tweet might be included in both corpora, however the vast majority of tweets is different across two corpora.Files are in the jsonl format
corpus; cybersecurity; NER