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finer-139

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named-entity-recognition

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nlpaueb commited on Mar 30, 2022

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 ### Dataset Summary
 **FiNER-139** is comprised of 1.1M sentences annotated with **eXtensive Business Reporting Language (XBRL)** tags extracted from annual and quarterly reports of publicly-traded companies in the US.
 Unlike other entity extraction tasks, like named entity recognition (NER) or contract element extraction, which typically require identifying entities of a small set of common types (e.g., persons, organizations), FiNER-139 uses a much larger label set of **139 entity types**.
 Another important difference from typical entity extraction is that FiNER focuses on numeric tokens, with the correct tag depending mostly on context, not the token itself.
 ### Supported Tasks

 ### Dataset Summary
+<div style="text-align: justify">
 **FiNER-139** is comprised of 1.1M sentences annotated with **eXtensive Business Reporting Language (XBRL)** tags extracted from annual and quarterly reports of publicly-traded companies in the US.
 Unlike other entity extraction tasks, like named entity recognition (NER) or contract element extraction, which typically require identifying entities of a small set of common types (e.g., persons, organizations), FiNER-139 uses a much larger label set of **139 entity types**.
 Another important difference from typical entity extraction is that FiNER focuses on numeric tokens, with the correct tag depending mostly on context, not the token itself.
+</div>
 ### Supported Tasks