Update README.md

README.md

@@ -70,7 +70,7 @@ To facilitate research towards automated XBRL tagging we release FiNER-139.
 
 ### Languages
 
-**FiNER-139** is compiled from approximately. 10k annual and quarterly **English** reports
+**FiNER-139** is compiled from approximately 10k annual and quarterly **English** reports
 
 ## Dataset Structure
 
@@ -126,9 +126,9 @@ The dataset was curated by [Loukas et al. (2022)](https://arxiv.org/abs/2203.064
 
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-FiNER-139 is compiled from approximately. 10k annual and quarterly English reports (filings) of publicly traded companies downloaded from the [US Securities
+FiNER-139 is compiled from approximately 10k annual and quarterly English reports (filings) of publicly traded companies downloaded from the [US Securities
 and Exchange Commission's (SEC)](https://www.sec.gov/) [Electronic Data Gathering, Analysis, and Retrieval (EDGAR)](https://www.sec.gov/edgar.shtml) system.
-The reports span a 5-year period, from 2016 to 2020. They are annotated with XBRL tags by professional auditors and describe the performance and projections of the companies. XBRL defines approximately. 6k entity types from the US-GAAP taxonomy. FiNER-139 is annotated with the 139 most frequent XBRL entity types with at least 1,000 appearances.
+The reports span a 5-year period, from 2016 to 2020. They are annotated with XBRL tags by professional auditors and describe the performance and projections of the companies. XBRL defines approximately 6k entity types from the US-GAAP taxonomy. FiNER-139 is annotated with the 139 most frequent XBRL entity types with at least 1,000 appearances.
 We used regular expressions to extract the text notes from the Financial Statements Item of each filing, which is the primary source of XBRL tags in annual and quarterly reports. We used the <strong>IOB2</strong> annotation scheme to distinguish tokens at the beginning, inside, or outside of tagged expressions, which leads to 279 possible token labels.
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