source_sample_idx int64 1 6.59k | context_id int64 1 6.59k | split stringclasses 1
value | query stringlengths 1.7k 16.5k | answer stringlengths 55 9.29k | context stringlengths 24 14.8k | output_entities listlengths 1 157 |
|---|---|---|---|---|---|---|
1 | 1 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "62", "datatype": "monetaryItemType"}, {"numeric_entity": "171", "datatype": "monetaryItemType"}, {"numeric_entity": "396", "datatype": "monetaryItemType"}, {"numeric_entity": "412", "datatype": "monetaryItemType"}, {"numeric_entity": "345", "datatype": "monetaryItemType"}, {"numeric_entity": "324",... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Provision for Income Taxes Provision for Income Taxes</td><td>For the years ended December 31</td></tr><tr><td></td><td>2024</td><td>2023</td><td>2022</td></tr><tr><td>Current</td><td></td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "62"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "171"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "396"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "412"
},
{
"datatype": "moneta... |
2 | 2 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "8068", "datatype": "monetaryItemType"}, {"numeric_entity": "8060", "datatype": "monetaryItemType"}, {"numeric_entity": "8042", "datatype": "monetaryItemType"}] | As of December 31, 2024, 2023 and 2022, the Company had a liability of $ 8,068 , $ 8,060 and $ 8,042 , respectively, representing the December 31, 2024, 2023 and 2022 fair values, respectively, of outstanding Progressive Waste restricted share units which are expected to be cash settled. All remaining unvested Progress... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "8068"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "8060"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "8042"
}
] |
7 | 7 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "1.7", "datatype": "monetaryItemType"}, {"numeric_entity": "0.2", "datatype": "monetaryItemType"}, {"numeric_entity": "0.7", "datatype": "monetaryItemType"}, {"numeric_entity": "1.7", "datatype": "monetaryItemType"}, {"numeric_entity": "0.2", "datatype": "monetaryItemType"}, {"numeric_entity": "0.7"... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>Years Ended December 31,</td></tr><tr><td></td><td></td><td>2024</td><td></td><td>2023</t... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "1.7"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "0.2"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "0.7"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1.7"
},
{
"datatype": "monet... |
19 | 19 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "6019", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "95148", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "105393", "datatype": "monetaryItemType"}, {"numeric_entity": "10... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "6019"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "95148"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "moneta... |
21 | 21 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "two", "datatype": "integerItemType"}] | The “Other” columns presented in the previous table, represent amounts that are not allocated to our two lines of business. The following provides additional information about the items included in the line of business results “Other” column for the periods indicated. | [
{
"datatype": "integerItemType",
"numeric_entity": "two"
}
] |
24 | 24 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "462", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "1", "datatype": "monetaryItemType"}, {"numeric_entity": "461", "datatype": "monetaryItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(in millions)</td><td>Amount</td></tr><tr><td>Balance at December 31, 2022</td><td>$</td><td>462</td><td></td></tr><tr><td>Additions</td><td>—</td><td></td></tr><tr><td>Balance at December 31, 2023</td><td>$</td><td>462</td><td></td></tr><tr>... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "462"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "461"
}
] |
27 | 27 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "3774239", "datatype": "monetaryItemType"}, {"numeric_entity": "3691066", "datatype": "monetaryItemType"}, {"numeric_entity": "3583978", "datatype": "monetaryItemType"}, {"numeric_entity": "564602", "datatype": "monetaryItemType"}, {"numeric_entity": "164489", "datatype": "monetaryItemType"}, {"nume... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>2024</td><td></td><td>2023</td><td></td><td>2022</td></tr><tr><td>Reconciliation of real estate, at cost:</td><td></td><td></... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "3774239"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "3691066"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "3583978"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "564602"
},
{
"da... |
29 | 29 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "3.20", "datatype": "percentItemType"}, {"numeric_entity": "3.26", "datatype": "percentItemType"}, {"numeric_entity": "3.21", "datatype": "percentItemType"}, {"numeric_entity": "2.52", "datatype": "percentItemType"}, {"numeric_entity": "2.62", "datatype": "percentItemType"}, {"numeric_entity": "2.75... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>2024</td><td></td><td>2023</td><td></td><td>2022</td></tr><tr><td>PPL</td><td>3.20</td><td>%</td><td></td><td>3.26</td><td>%<... | [
{
"datatype": "percentItemType",
"numeric_entity": "3.20"
},
{
"datatype": "percentItemType",
"numeric_entity": "3.26"
},
{
"datatype": "percentItemType",
"numeric_entity": "3.21"
},
{
"datatype": "percentItemType",
"numeric_entity": "2.52"
},
{
"datatype": "perce... |
31 | 31 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "249.3", "datatype": "monetaryItemType"}, {"numeric_entity": "208.8", "datatype": "monetaryItemType"}, {"numeric_entity": "167.6", "datatype": "monetaryItemType"}, {"numeric_entity": "272.2", "datatype": "monetaryItemType"}, {"numeric_entity": "255.5", "datatype": "monetaryItemType"}, {"numeric_enti... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>Years Ended December 31,</td></tr><tr><td></td><td></td><td>2024</td><td></td><td>2023</t... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "249.3"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "208.8"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "167.6"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "272.2"
},
{
"datatype"... |
37 | 37 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "5104017", "datatype": "sharesItemType"}, {"numeric_entity": "67917432", "datatype": "sharesItemType"}] | Immediately prior to the completion of our IPO, all of our then-outstanding shares of convertible preferred stock were automatically converted into 5,104,017 and 67,917,432 shares of our Class A and Class B common stock, respectively. | [
{
"datatype": "sharesItemType",
"numeric_entity": "5104017"
},
{
"datatype": "sharesItemType",
"numeric_entity": "67917432"
}
] |
58 | 58 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "30.4", "datatype": "monetaryItemType"}, {"numeric_entity": "67.1", "datatype": "monetaryItemType"}, {"numeric_entity": "58.9", "datatype": "monetaryItemType"}, {"numeric_entity": "82.2", "datatype": "monetaryItemType"}, {"numeric_entity": "134.1", "datatype": "monetaryItemType"}, {"numeric_entity":... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>December 31,</td></tr><tr><td></td><td></td><td>2024</td><td></td><td>2023</td></tr><tr><td>CURRENT ASSETS</td><td></td><td></td><td></td><td><... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "30.4"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "67.1"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "58.9"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "82.2"
},
{
"datatype": "m... |
62 | 62 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "464170000", "datatype": "sharesItemType"}, {"numeric_entity": "1000000", "datatype": "sharesItemType"}] | - Payment of dividends on our common stock is also subject to the prior payment of dividends on our 24 series of preferred stock and one series of senior preferred stock, representing an aggregate of 464,170,000 shares and 1,000,000 shares outstanding, respectively, as of December 31, 2024. Payment of dividends on all ... | [
{
"datatype": "sharesItemType",
"numeric_entity": "464170000"
},
{
"datatype": "sharesItemType",
"numeric_entity": "1000000"
}
] |
63 | 63 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "357", "datatype": "monetaryItemType"}, {"numeric_entity": "252", "datatype": "monetaryItemType"}, {"numeric_entity": "21", "datatype": "monetaryItemType"}, {"numeric_entity": "24", "datatype": "monetaryItemType"}, {"numeric_entity": "29", "datatype": "monetaryItemType"}, {"numeric_entity": "35", "d... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>December 31,</td></tr><tr><td>(in millions)</td><td>2024</td><td></td><td>2023</td></tr><tr><td>Deferred tax assets:</td><td></td><td></td><td></td></tr><tr><td>Net operating loss... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "357"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "252"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "21"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "24"
},
{
"datatype": "monetar... |
88 | 88 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "1.25", "datatype": "monetaryItemType"}, {"numeric_entity": "100", "datatype": "monetaryItemType"}] | Issuances under the PPL Capital Funding and RIE commercial paper programs are supported by the PPL Capital Funding syndicated credit facility, which, at December 31, 2024, had a total capacity of $ 1.25 billion and under which they are both borrowers. PPL Capital Funding’s Commercial paper program is also backed by a s... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "1.25"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "100"
}
] |
97 | 97 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "36", "datatype": "monetaryItemType"}, {"numeric_entity": "43", "datatype": "monetaryItemType"}, {"numeric_entity": "11", "datatype": "monetaryItemType"}, {"numeric_entity": "12", "datatype": "monetaryItemType"}, {"numeric_entity": "6", "datatype": "monetaryItemType"}, {"numeric_entity": "8", "datat... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(in millions)</td><td></td><td>Investments in Unconsolidated VIEs</td><td></td><td>Maximum Exposure to Loss</td></tr><tr><td>NQ Fund V</td><td></td><td>$</td><td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "36"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "43"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "11"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "12"
},
{
"datatype": "monetaryI... |
107 | 107 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "79.8", "datatype": "monetaryItemType"}] | and $ 79.8 million, respectively, | [
{
"datatype": "monetaryItemType",
"numeric_entity": "79.8"
}
] |
113 | 113 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "485", "datatype": "monetaryItemType"}, {"numeric_entity": "499", "datatype": "monetaryItemType"}, {"numeric_entity": "480", "datatype": "monetaryItemType"}] | The Company sponsors a 401(k) retirement savings plan covering all eligible employees. The Company makes a discretionary matching contribution on a portion of employee participant salaries and, based on its profitability, may make an additional discretionary contribution at each fiscal year end to all eligible employee... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "485"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "499"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "480"
}
] |
124 | 124 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "13883", "datatype": "monetaryItemType"}, {"numeric_entity": "15357", "datatype": "monetaryItemType"}, {"numeric_entity": "15569", "datatype": "monetaryItemType"}, {"numeric_entity": "15737", "datatype": "monetaryItemType"}, {"numeric_entity": "14310", "datatype": "monetaryItemType"}, {"numeric_enti... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Operating Leases</td></tr><tr><td>2025</td><td>$</td><td>13,883</td><td></td></tr><tr><td>2026</td><td>15,357</td><td></td></tr><tr><td>2027</td><td>15,569</td><td></td></tr><tr><td>2028</td><td>15,737</td><td></td></tr><tr><td>2029<... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "13883"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "15357"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "15569"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "15737"
},
{
"datatype"... |
137 | 137 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "94", "datatype": "monetaryItemType"}, {"numeric_entity": "96", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "88", "datatype": "monetaryItemType"}, {"numeric_entity": "90", "datat... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>U.S. Plan U.S. Plan</td><td></td><td>Non-U.S. Plans</td></tr><tr><td></... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "94"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "96"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "monetaryIte... |
138 | 138 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "898.6", "datatype": "monetaryItemType"}, {"numeric_entity": "878.2", "datatype": "monetaryItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>Carrying Amount of the Hedged Liabi... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "898.6"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "878.2"
}
] |
139 | 139 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "23", "datatype": "monetaryItemType"}, {"numeric_entity": "29", "datatype": "monetaryItemType"}, {"numeric_entity": "69", "datatype": "monetaryItemType"}, {"numeric_entity": "71", "datatype": "monetaryItemType"}, {"numeric_entity": "2", "datatype": "monetaryItemType"}, {"numeric_entity": "3", "datat... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td></tr><tr><td>Current and Non-current Financing Receivables Current and Non-current Financing Receivables</td><td>As of</td></tr><tr><td></td><td>December 31, 2024</td><td>December 31, 2023</td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "23"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "29"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "69"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "71"
},
{
"datatype": "monetaryI... |
152 | 152 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "197.9", "datatype": "monetaryItemType"}, {"numeric_entity": "40.2", "datatype": "monetaryItemType"}, {"numeric_entity": "37.5", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "26.5", "datatype": "monetaryItemType"}, {"numeric_entity": "3... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>Total Federal</td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "197.9"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "40.2"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "37.5"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "mon... |
175 | 175 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "37818", "datatype": "sharesItemType"}, {"numeric_entity": "308", "datatype": "monetaryItemType"}, {"numeric_entity": "2957", "datatype": "monetaryItemType"}, {"numeric_entity": "663", "datatype": "monetaryItemType"}, {"numeric_entity": "3928", "datatype": "monetaryItemType"}, {"numeric_entity": "32... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Common stock shar... | [
{
"datatype": "sharesItemType",
"numeric_entity": "37818"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "308"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "2957"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "663"
},
{
"datatype": "mone... |
180 | 180 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "321.2", "datatype": "monetaryItemType"}, {"numeric_entity": "838.8", "datatype": "monetaryItemType"}, {"numeric_entity": "1686.3", "datatype": "monetaryItemType"}, {"numeric_entity": "2846.3", "datatype": "monetaryItemType"}, {"numeric_entity": "45.0", "datatype": "monetaryItemType"}, {"numeric_ent... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Common Stock</td><td></td><td>Paid-in Capital</td><td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "321.2"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "838.8"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1686.3"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "2846.3"
},
{
"datatyp... |
194 | 194 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "2681", "datatype": "monetaryItemType"}, {"numeric_entity": "2653", "datatype": "monetaryItemType"}, {"numeric_entity": "1210", "datatype": "monetaryItemType"}, {"numeric_entity": "1326", "datatype": "monetaryItemType"}, {"numeric_entity": "1", "datatype": "monetaryItemType"}, {"numeric_entity": "2"... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>U.S. Plan U.S. Plan</td><td></td><td>Non-U.S. Plans</td></tr><tr><td></... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "2681"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "2653"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1210"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1326"
},
{
"datatype": "m... |
198 | 198 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "67781", "datatype": "monetaryItemType"}, {"numeric_entity": "10229", "datatype": "monetaryItemType"}, {"numeric_entity": "57552", "datatype": "monetaryItemType"}, {"numeric_entity": "58373", "datatype": "monetaryItemType"}, {"numeric_entity": "25766", "datatype": "monetaryItemType"}, {"numeric_enti... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Gross Carrying Value</td><td></td><td>Accumulated Amortization</td><td></td><td>Net Carrying Value</td></tr><tr><td>Customer ... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "67781"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "10229"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "57552"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "58373"
},
{
"datatype"... |
200 | 200 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "37922", "datatype": "monetaryItemType"}, {"numeric_entity": "37922", "datatype": "monetaryItemType"}, {"numeric_entity": "23863", "datatype": "monetaryItemType"}, {"numeric_entity": "23863", "datatype": "monetaryItemType"}, {"numeric_entity": "107307", "datatype": "monetaryItemType"}, {"numeric_ent... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>2024</td><td></td><td>2023</td><td></td><td>2022</td></tr><tr><td>DILUTED:</td><td></td><td></td><td></td><td></td><td></td><... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "37922"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "37922"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "23863"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "23863"
},
{
"datatype"... |
212 | 212 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "75", "datatype": "percentItemType"}, {"numeric_entity": "51", "datatype": "percentItemType"}, {"numeric_entity": "462", "datatype": "monetaryItemType"}] | On February 20, 2024, the Company's wholly-owned subsidiary, Whirlpool Mauritius Limited ("Seller"), executed the sale of 30.4 million equity shares of Whirlpool India via an on-market trade. The sale, which was accounted for as an equity transaction, reduced Seller's ownership in Whirlpool India from 75 % to 51 %, and... | [
{
"datatype": "percentItemType",
"numeric_entity": "75"
},
{
"datatype": "percentItemType",
"numeric_entity": "51"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "462"
}
] |
218 | 218 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "137", "datatype": "monetaryItemType"}, {"numeric_entity": "134", "datatype": "monetaryItemType"}, {"numeric_entity": "1", "datatype": "monetaryItemType"}, {"numeric_entity": "7", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "7", "datat... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Pension</td><td></td><td>Postretirement</td></tr><tr><td></td><td>2024<... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "137"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "134"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "7"
},
{
"datatype": "monetaryI... |
226 | 226 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "2.65", "datatype": "monetaryItemType"}, {"numeric_entity": "2.68", "datatype": "monetaryItemType"}, {"numeric_entity": "1.07", "datatype": "monetaryItemType"}, {"numeric_entity": "1.10", "datatype": "monetaryItemType"}, {"numeric_entity": "44", "datatype": "monetaryItemType"}, {"numeric_entity": "4... | Included in the claims and claim adjustment expense reserves are reserves for long-term disability and annuity claim payments, primarily arising from workers’ compensation insurance and workers’ compensation excess insurance policies, that are discounted to the present value of the estimated future payments. The disco... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "2.65"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "2.68"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1.07"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1.10"
},
{
"datatype": "m... |
232 | 232 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "1837.8", "datatype": "monetaryItemType"}, {"numeric_entity": "1673.5", "datatype": "monetaryItemType"}, {"numeric_entity": "1286.3", "datatype": "monetaryItemType"}, {"numeric_entity": "133.4", "datatype": "monetaryItemType"}, {"numeric_entity": "78.4", "datatype": "monetaryItemType"}, {"numeric_en... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>Years Ended December 31,</td></tr><tr><td>Cash Flow Information</td><td></td><td>2024</td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "1837.8"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1673.5"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1286.3"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "133.4"
},
{
"dataty... |
255 | 255 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "6", "datatype": "integerItemType"}, {"numeric_entity": "26.4", "datatype": "monetaryItemType"}, {"numeric_entity": "4", "datatype": "integerItemType"}, {"numeric_entity": "114.8", "datatype": "monetaryItemType"}, {"numeric_entity": "1", "datatype": "integerItemType"}, {"numeric_entity": "13.7", "da... | <table><tr><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td></tr><tr><td> </td><td> </td><td>Number of</td><td> </td><td> </td><td> </td><td>Total Real Estate</td><td>... | [
{
"datatype": "integerItemType",
"numeric_entity": "6"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "26.4"
},
{
"datatype": "integerItemType",
"numeric_entity": "4"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "114.8"
},
{
"datatype": "integerI... |
269 | 269 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "50.1", "datatype": "monetaryItemType"}, {"numeric_entity": "18.2", "datatype": "monetaryItemType"}, {"numeric_entity": "25.0", "datatype": "monetaryItemType"}] | In the third quarter of 2022, the Company also acquired all of the issued and outstanding membership interests of Ripley Tools, LLC and Nooks Hill Road, LLC (collectively, “Ripley Tools”) for a cash purchase price of approximately $ 50.1 million, net of cash acquired. Ripley Tools is a leading manufacturer of cable and... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "50.1"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "18.2"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "25.0"
}
] |
289 | 289 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "121.7", "datatype": "monetaryItemType"}, {"numeric_entity": "178.9", "datatype": "monetaryItemType"}, {"numeric_entity": "131.3", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "0.1", "datatype": "monetaryItemType"}, {"numeric_entity": "... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Year Ended December 31</td><td>2024</td><td>2023</td><td>2022</td></tr><tr><td>Millions</td><td></td><td></td><td></td></tr><tr><td>Net Income</td><td>$ 121.7</td><td></td><td>$ 178.9</td>... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "121.7"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "178.9"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "131.3"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "m... |
290 | 290 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "8", "datatype": "monetaryItemType"}, {"numeric_entity": "6", "datatype": "monetaryItemType"}, {"numeric_entity": "2", "datatype": "monetaryItemType"}] | In connection with the November 2023 Notes Refinancing, we incurred $ 8 million in third party fees, of which $ 6 million was paid concurrently with the issuance, and $ 1 million was accrued. We also recorded a $ 2 million loss on extinguishment of debt relating to the write off of unamortized deferred financing costs ... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "8"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "6"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "2"
}
] |
296 | 296 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "3.72", "datatype": "monetaryItemType"}] | In 2024, we purchased $ 3.72 billion of collateralized loan obligations in loan form, which were all investment grade as of December 31, 2024. | [
{
"datatype": "monetaryItemType",
"numeric_entity": "3.72"
}
] |
301 | 301 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "3.7", "datatype": "percentItemType"}, {"numeric_entity": "2.9", "datatype": "percentItemType"}, {"numeric_entity": "2.7", "datatype": "percentItemType"}, {"numeric_entity": "2.2", "datatype": "percentItemType"}, {"numeric_entity": "2.3", "datatype": "percentItemType"}, {"numeric_entity": "6.7", "da... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td... | [
{
"datatype": "percentItemType",
"numeric_entity": "3.7"
},
{
"datatype": "percentItemType",
"numeric_entity": "2.9"
},
{
"datatype": "percentItemType",
"numeric_entity": "2.7"
},
{
"datatype": "percentItemType",
"numeric_entity": "2.2"
},
{
"datatype": "percentIt... |
309 | 309 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "1845", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Remaining Capacity</td><td></td><td>Availability Under Borrowing Base Limitation</td></tr><tr><td>ABL Credit Facility</td><td>$</td><td>1,845</td><td></td><td></td><td>$</td><td>1... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "1845"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
}
] |
317 | 317 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "127366", "datatype": "monetaryItemType"}, {"numeric_entity": "64105", "datatype": "monetaryItemType"}, {"numeric_entity": "86321", "datatype": "monetaryItemType"}, {"numeric_entity": "298726", "datatype": "monetaryItemType"}, {"numeric_entity": "218035", "datatype": "monetaryItemType"}, {"numeric_e... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Years Ended</td></tr><tr><td></td><td>December 31, 2024</td><td></td><td>December 31, 2023</td><td></td><td>December 31, 2022... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "127366"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "64105"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "86321"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "298726"
},
{
"datatyp... |
321 | 321 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "2550", "datatype": "sharesItemType"}, {"numeric_entity": "25.80", "datatype": "perShareItemType"}, {"numeric_entity": "1562", "datatype": "sharesItemType"}, {"numeric_entity": "40.21", "datatype": "perShareItemType"}, {"numeric_entity": "152", "datatype": "sharesItemType"}, {"numeric_entity": "32.8... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>RSUs</td><td></td><td>Weighted- Average Grant Date Fair Value Per RSU</td></tr><tr><td></td><td></td><td>(In thousands)</td><td></td><td></td><... | [
{
"datatype": "sharesItemType",
"numeric_entity": "2550"
},
{
"datatype": "perShareItemType",
"numeric_entity": "25.80"
},
{
"datatype": "sharesItemType",
"numeric_entity": "1562"
},
{
"datatype": "perShareItemType",
"numeric_entity": "40.21"
},
{
"datatype": "sha... |
328 | 328 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "1100614", "datatype": "monetaryItemType"}, {"numeric_entity": "1199282", "datatype": "monetaryItemType"}, {"numeric_entity": "243349", "datatype": "monetaryItemType"}, {"numeric_entity": "195129", "datatype": "monetaryItemType"}, {"numeric_entity": "2738374", "datatype": "monetaryItemType"}, {"nume... | <table><tr><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td>... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "1100614"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1199282"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "243349"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "195129"
},
{
"dat... |
329 | 329 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "six", "datatype": "integerItemType"}, {"numeric_entity": "six", "datatype": "integerItemType"}] | The Company manages its operations through the following six geographic solid waste operating segments: Western, Southern, Eastern, Central, Canada and MidSouth. The Company’s six geographic solid waste operating segments comprise its reportable segments. Each operating segment is responsible for managing several vert... | [
{
"datatype": "integerItemType",
"numeric_entity": "six"
},
{
"datatype": "integerItemType",
"numeric_entity": "six"
}
] |
332 | 332 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "106.04", "datatype": "perShareItemType"}, {"numeric_entity": "112.73", "datatype": "perShareItemType"}, {"numeric_entity": "120.25", "datatype": "perShareItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>2024</td><td></td><td>2023</td><td></td><td>2022</td></tr><tr><td></td><td>(In millions, except per share amounts)</td></tr><... | [
{
"datatype": "perShareItemType",
"numeric_entity": "106.04"
},
{
"datatype": "perShareItemType",
"numeric_entity": "112.73"
},
{
"datatype": "perShareItemType",
"numeric_entity": "120.25"
}
] |
339 | 339 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "992478", "datatype": "sharesItemType"}, {"numeric_entity": "195", "datatype": "monetaryItemType"}] | As of December 31, 2024, there are 992,478 performance awards outstanding with an intrinsic value of approximately $ 195 million. | [
{
"datatype": "sharesItemType",
"numeric_entity": "992478"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "195"
}
] |
340 | 340 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "21964", "datatype": "monetaryItemType"}, {"numeric_entity": "11032", "datatype": "monetaryItemType"}, {"numeric_entity": "11407", "datatype": "monetaryItemType"}, {"numeric_entity": "6588", "datatype": "monetaryItemType"}, {"numeric_entity": "33171", "datatype": "monetaryItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Year Ended December 31,</td></tr><tr><td></td><td>2024</td><td></td><td>2023</td></tr><tr><td>Beginning of period</td><td>$</td><td>21,964</td><td></td><td></td><td>$</td><td>11,0... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "21964"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "11032"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "11407"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "6588"
},
{
"datatype":... |
346 | 346 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "81.5", "datatype": "monetaryItemType"}, {"numeric_entity": "6.8", "datatype": "monetaryItemType"}, {"numeric_entity": "8.0", "datatype": "monetaryItemType"}, {"numeric_entity": "10.7", "datatype": "monetaryItemType"}, {"numeric_entity": "7.9", "datatype": "monetaryItemType"}, {"numeric_entity": "5.... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "81.5"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "6.8"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "8.0"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "10.7"
},
{
"datatype": "mon... |
348 | 348 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "783.5", "datatype": "monetaryItemType"}, {"numeric_entity": "766.0", "datatype": "monetaryItemType"}, {"numeric_entity": "516.8", "datatype": "monetaryItemType"}, {"numeric_entity": "212.1", "datatype": "monetaryItemType"}, {"numeric_entity": "149.7", "datatype": "monetaryItemType"}, {"numeric_enti... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Year Ended December 31,</td></tr><tr><td>(in millions)</td><td>2024</td><td>2023</td><td>2022</td></tr><tr><td>Cash Flows from Operating Activities of Continuing Operations</td><t... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "783.5"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "766.0"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "516.8"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "212.1"
},
{
"datatype"... |
350 | 350 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "381", "datatype": "monetaryItemType"}] | trademark exceeded its fair value (Level 3 input) by $ 381 million. A discount rate of 12.5 % and a royalty rate of 4.0 % were utilized in that assessment. The brand has been unfavorably impacted as Whirlpool has refocused its brand strategy to the laundry category. | [
{
"datatype": "monetaryItemType",
"numeric_entity": "381"
}
] |
353 | 353 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "one", "datatype": "integerItemType"}] | who makes operating decisions, allocates resources to and assesses performance based on these operating segments. The State Transcos operating segments all have similar economic characteristics and meet all of the criteria under the accounting guidance for “Segment Reporting” to be aggregated into one reportable segme... | [
{
"datatype": "integerItemType",
"numeric_entity": "one"
}
] |
355 | 355 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "888856", "datatype": "sharesItemType"}, {"numeric_entity": "228.55", "datatype": "perShareItemType"}, {"numeric_entity": "594957", "datatype": "sharesItemType"}, {"numeric_entity": "216.78", "datatype": "perShareItemType"}, {"numeric_entity": "415766", "datatype": "sharesItemType"}, {"numeric_entit... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td> Number of RSUs</td><td></td><td>Weighted Average Grant-Date Fair Value</td></tr><tr><td>Outstanding as of December 31, 2023</td><td></td><td>8... | [
{
"datatype": "sharesItemType",
"numeric_entity": "888856"
},
{
"datatype": "perShareItemType",
"numeric_entity": "228.55"
},
{
"datatype": "sharesItemType",
"numeric_entity": "594957"
},
{
"datatype": "perShareItemType",
"numeric_entity": "216.78"
},
{
"datatype"... |
362 | 362 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "10.8", "datatype": "percentItemType"}] | In January 2024, PSO filed a request with the OCC for a $ 218 million annual base rate increase based upon a 10.8 % ROE with a capital structure of 48.9 % debt and 51.1 % common equity. PSO requested an expanded transmission cost recovery rider and a mechanism to recover generation costs necessary to comply with SPP’s... | [
{
"datatype": "percentItemType",
"numeric_entity": "10.8"
}
] |
365 | 365 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "659", "datatype": "monetaryItemType"}, {"numeric_entity": "532", "datatype": "monetaryItemType"}, {"numeric_entity": "708", "datatype": "monetaryItemType"}, {"numeric_entity": "665", "datatype": "monetaryItemType"}, {"numeric_entity": "833", "datatype": "monetaryItemType"}, {"numeric_entity": "772"... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(at December 31, in millions)</td><td></td><td>2024</td><td></td><td>2023</td></tr><tr><td>Deferred tax assets</td><td></td><td></td><td></td><td></td></tr><tr><... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "659"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "532"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "708"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "665"
},
{
"datatype": "monet... |
366 | 366 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "407", "datatype": "monetaryItemType"}, {"numeric_entity": "266", "datatype": "monetaryItemType"}, {"numeric_entity": "141", "datatype": "monetaryItemType"}, {"numeric_entity": "493", "datatype": "monetaryItemType"}, {"numeric_entity": "318", "datatype": "monetaryItemType"}, {"numeric_entity": "175"... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "407"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "266"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "141"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "493"
},
{
"datatype": "monet... |
384 | 384 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "4.4", "datatype": "sharesItemType"}, {"numeric_entity": "1.0", "datatype": "monetaryItemType"}, {"numeric_entity": "225.44", "datatype": "perShareItemType"}, {"numeric_entity": "5.04", "datatype": "monetaryItemType"}] | The Company’s Board of Directors has approved common share repurchase authorizations under which repurchases may be made from time to time in the open market, pursuant to pre-set trading plans meeting the requirements of Rule 10b5-1 under the Securities Exchange Act of 1934, in private transactions or otherwise. The a... | [
{
"datatype": "sharesItemType",
"numeric_entity": "4.4"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1.0"
},
{
"datatype": "perShareItemType",
"numeric_entity": "225.44"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "5.04"
}
] |
388 | 388 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "18", "datatype": "percentItemType"}, {"numeric_entity": "17", "datatype": "percentItemType"}, {"numeric_entity": "16", "datatype": "percentItemType"}, {"numeric_entity": "15", "datatype": "percentItemType"}, {"numeric_entity": "100", "datatype": "percentItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>Mortgage Insurance Coverage (1) Mortgage Insurance Coverage (1)</td></tr><tr><td>Mortgage Insurer</td><td></td><td>December 31, 2024</td><td></td></tr><tr><td>Mortgage Guaranty Insurance C... | [
{
"datatype": "percentItemType",
"numeric_entity": "18"
},
{
"datatype": "percentItemType",
"numeric_entity": "17"
},
{
"datatype": "percentItemType",
"numeric_entity": "16"
},
{
"datatype": "percentItemType",
"numeric_entity": "15"
},
{
"datatype": "percentItemTy... |
405 | 405 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "no", "datatype": "monetaryItemType"}, {"numeric_entity": "6", "datatype": "monetaryItemType"}, {"numeric_entity": "no", "datatype": "monetaryItemType"}] | In 2024, we contributed $ 7 million to our non-U.S. pension plans. We did no t contribute to our U.S. pension plan. We estimate that 2025 pension contributions will be approximately $ 6 million to our non-U.S. pension plans. We do no t plan to make contributions to our U.S. pension plan in 2025. Estimated future contri... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "no"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "6"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "no"
}
] |
410 | 410 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "22.4", "datatype": "monetaryItemType"}, {"numeric_entity": "3.1", "datatype": "monetaryItemType"}, {"numeric_entity": "0.4", "datatype": "monetaryItemType"}, {"numeric_entity": "18.9", "datatype": "monetaryItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Recurring Fair Value Measures</td><td></td><td></td><td></td></tr><tr><td>Activity in Level 3</td><td></td><td></td><td>Real Estate</td></tr><tr><td>Millions</td><td></td><td></td><td></td></tr><tr><td>Bala... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "22.4"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "3.1"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "0.4"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "18.9"
}
] |
458 | 458 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "5", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "15", "datatype": "monetaryItemType"}, {"numeric_entity": "19", "datatype": "monetaryItemType"}, {"numeric_entity": "16", "datatype": "monetaryItemType"}, {"numeric_entity": "3", "dataty... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>Fair value measurements at</td></tr... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "5"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "15"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "19"
},
{
"datatype": "monetaryIte... |
463 | 463 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "0.8", "datatype": "monetaryItemType"}, {"numeric_entity": "52.7", "datatype": "monetaryItemType"}, {"numeric_entity": "4.4", "datatype": "monetaryItemType"}] | (1) In October 2023, we entered into a group annuity contract from an insurance company to provide for the payment of pension benefits to select NorthWestern Energy MT Pension Plan participants. We purchased the contract with $ 51.9 million of plan assets in 2023. A trailing premium of $ 0.8 million related to final da... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "0.8"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "52.7"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "4.4"
}
] |
468 | 468 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "495", "datatype": "monetaryItemType"}, {"numeric_entity": "200", "datatype": "monetaryItemType"}, {"numeric_entity": "295", "datatype": "monetaryItemType"}, {"numeric_entity": "200", "datatype": "monetaryItemType"}, {"numeric_entity": "110", "datatype": "monetaryItemType"}] | In March 2023, as a precaution to ensure we maintained liquidity during the uncertainty of the banking crisis that followed the failure of Silicon Valley Bank, we drew down the available $ 495 million of capacity under our 2021 Revolver. As concerns about market liquidity subsided, we repaid $ 200 million in March and ... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "495"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "200"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "295"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "200"
},
{
"datatype": "monet... |
472 | 472 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "50", "datatype": "monetaryItemType"}, {"numeric_entity": "79", "datatype": "monetaryItemType"}, {"numeric_entity": "110", "datatype": "monetaryItemType"}, {"numeric_entity": "125", "datatype": "monetaryItemType"}, {"numeric_entity": "139", "datatype": "monetaryItemType"}, {"numeric_entity": "25", "... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "50"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "79"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "110"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "125"
},
{
"datatype": "monetar... |
477 | 477 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "2434", "datatype": "monetaryItemType"}, {"numeric_entity": "3649", "datatype": "monetaryItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>December 31,</td></tr><tr><td></td><td>2024</td><td></td><td>2023</td></tr><tr><td>Beginning QF liability</td><td>$</td><td>28,670</td><td></td><td></td><td>$</td><td>49,728</td><... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "2434"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "3649"
}
] |
478 | 478 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "7.0", "datatype": "monetaryItemType"}, {"numeric_entity": "1.8", "datatype": "monetaryItemType"}] | During 2022, the Company recognized $ 7.0 million of settlement losses in continuing operations and $ 1.8 million of settlement losses in discontinued operations. Those settlement losses are the result of lump-sum distributions from the Company’s defined benefit pension plans which exceeded the threshold for settlement... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "7.0"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1.8"
}
] |
479 | 479 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "1165", "datatype": "monetaryItemType"}, {"numeric_entity": "978", "datatype": "monetaryItemType"}, {"numeric_entity": "5534", "datatype": "monetaryItemType"}, {"numeric_entity": "6019", "datatype": "monetaryItemType"}, {"numeric_entity": "100118", "datatype": "monetaryItemType"}, {"numeric_entity":... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>December 31,</td></tr><tr><td>( In millions , except share-related amounts) ( In millions , except share-related amounts)</td><td></td><td>2024</td><td>2023</td></tr><tr>... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "1165"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "978"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "5534"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "6019"
},
{
"datatype": "mo... |
483 | 483 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "551", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "300", "datatype": "monetaryItemType"}, {"numeric_entity": "250", "datatype": "monetaryItemType"}, {"numeric_entity": "904", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "d... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>PPL</td><td></td><td>PPL Electric</td><td></td><td></... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "551"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "300"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "250"
},
{
"datatype": "monetar... |
488 | 488 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "24", "datatype": "monetaryItemType"}, {"numeric_entity": "24", "datatype": "monetaryItemType"}, {"numeric_entity": "24", "datatype": "monetaryItemType"}, {"numeric_entity": "24", "datatype": "monetaryItemType"}, {"numeric_entity": "24", "datatype": "monetaryItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Millions of dollars</td><td></td></tr><tr><td>2025</td><td>$</td><td>24</td><td></td></tr><tr><td>2026</td><td>24</td><td></td></tr><tr><td>2027</td><td>24</td><td></td></tr><tr><td>2028</td><td>24</td><td></td></tr><tr><td>2029</td><td>24</t... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "24"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "24"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "24"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "24"
},
{
"datatype": "monetaryI... |
497 | 497 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "500000", "datatype": "monetaryItemType"}, {"numeric_entity": "4.25", "datatype": "percentItemType"}, {"numeric_entity": "5792", "datatype": "monetaryItemType"}, {"numeric_entity": "100", "datatype": "percentItemType"}] | On November 16, 2018, the Company completed an underwritten public offering of $ 500,000 aggregate principal amount of 4.25 % Senior Notes due December 1, 2028 (the “2028 Senior Notes”). The 2028 Senior Notes were issued under the Indenture, dated as of November 16, 2018 (as amended, restated, amended and restated, sup... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "500000"
},
{
"datatype": "percentItemType",
"numeric_entity": "4.25"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "5792"
},
{
"datatype": "percentItemType",
"numeric_entity": "100"
}
] |
518 | 518 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "13.0", "datatype": "monetaryItemType"}, {"numeric_entity": "1.5", "datatype": "monetaryItemType"}, {"numeric_entity": "14.5", "datatype": "monetaryItemType"}, {"numeric_entity": "844.0", "datatype": "monetaryItemType"}, {"numeric_entity": "79... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>AEP Texas</td></tr><tr><td></td><td></td><td>December 31,</td><td></td><td>Remaining Refu... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "13.0"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1.5"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "14.5"
},
{
"datatype": "monet... |
519 | 519 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "246", "datatype": "monetaryItemType"}, {"numeric_entity": "229", "datatype": "monetaryItemType"}, {"numeric_entity": "4", "datatype": "monetaryItemType"}, {"numeric_entity": "5", "datatype": "monetaryItemType"}, {"numeric_entity": "250", "datatype": "monetaryItemType"}, {"numeric_entity": "234", "d... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>Year Ended December 31,</td></tr><tr><td></td><td></td><td>2024</td><td></td><td>2023</td></tr><tr><td>Non-U.S.</td><td></td><td>$</td><td>246<... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "246"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "229"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "4"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "5"
},
{
"datatype": "monetaryI... |
525 | 525 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "32", "datatype": "monetaryItemType"}] | In March 2024, APCo and WPCo (the Companies) submitted an annual MRBC surcharge update filing with the WVPSC requesting a $ 32 million annual increase in the Companies’ combined MRBC rates. The MRBC is an infrastructure investment tracker that allows limited cost recovery related to capital investments between the Com... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "32"
}
] |
540 | 540 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "8", "datatype": "monetaryItemType"}, {"numeric_entity": "18", "datatype": "monetaryItemType"}, {"numeric_entity": "3", "datatype": "monetaryItemType"}, {"numeric_entity": "6", "datatype": "monetaryItemType"}, {"numeric_entity": "134", "datatype": "monetaryItemType"}, {"numeric_entity": "116", "data... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>2024</td><td></td><td>2023</td></tr><tr><td>Assets</td><td></td><td></td><td></td></tr><tr><td>Current Assets</td><td></td><td></td><td></td></tr><tr><td>Cash and cash equivalents... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "8"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "18"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "3"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "6"
},
{
"datatype": "monetaryItem... |
543 | 543 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "11.7", "datatype": "monetaryItemType"}, {"numeric_entity": "18.0", "datatype": "monetaryItemType"}, {"numeric_entity": "10.0", "datatype": "percentItemType"}, {"numeric_entity": "three", "datatype": "integerItemType"}, {"numeric_entity": "one", "datatype": "integerItemType"}] | In January 2024, we funded $ 11.7 million under a new mortgage loan to a new operator. In June 2024, we amended the loan and funded an additional $ 18.0 million under the mortgage loan. The mortgage loan bears interest at 10.0 % and matures on January 31, 2027 . Interest is payable monthly in arrears and no principal p... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "11.7"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "18.0"
},
{
"datatype": "percentItemType",
"numeric_entity": "10.0"
},
{
"datatype": "integerItemType",
"numeric_entity": "three"
},
{
"datatype": "in... |
557 | 557 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "4.6", "datatype": "monetaryItemType"}, {"numeric_entity": "0.3", "datatype": "monetaryItemType"}, {"numeric_entity": "0.5", "datatype": "monetaryItemType"}, {"numeric_entity": "0.6", "datatype": "monetaryItemType"}, {"numeric_entity": "0.4", "datatype": "monetaryItemType"}, {"numeric_entity": "46.2... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "4.6"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "0.3"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "0.5"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "0.6"
},
{
"datatype": "monet... |
566 | 566 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "282", "datatype": "monetaryItemType"}, {"numeric_entity": "212", "datatype": "monetaryItemType"}, {"numeric_entity": "245", "datatype": "monetaryItemType"}, {"numeric_entity": "242", "datatype": "monetaryItemType"}, {"numeric_entity": "284", "datatype": "monetaryItemType"}, {"numeric_entity": "212"... | During the third quarter of 2024, the Company completed its annual in-depth asbestos claim review. While the latest available government data continue to reflect a declining trend in deaths caused by mesothelioma, the number of policyholders with open asbestos claims was relatively flat compared to 2023. Net asbestos... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "282"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "212"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "245"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "242"
},
{
"datatype": "monet... |
573 | 573 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "883", "datatype": "monetaryItemType"}, {"numeric_entity": "609", "datatype": "monetaryItemType"}, {"numeric_entity": "109", "datatype": "monetaryItemType"}, {"numeric_entity": "69", "datatype": "monetaryItemType"}, {"numeric_entity": "348", "datatype": "monetaryItemType"}, {"numeric_entity": "66", ... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>December 31,</td></tr><tr><td></td><td>2024</td><td></td><td>2023</td></tr><tr><td>Current liabilities:</td><td></td><td></td><td></td></tr><tr><td>Wages and employee benefits</td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "883"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "609"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "109"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "69"
},
{
"datatype": "moneta... |
574 | 574 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "2", "datatype": "monetaryItemType"}, {"numeric_entity": "—", "datatype": "monetaryItemType"}, {"numeric_entity": "2", "datatype": "monetaryItemType"}, {"numeric_entity": "9667", "datatype": "monetaryItemType"}, {"numeric_entity": "9669", "dat... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>December 31,</td></tr><tr><td>(in millions, except per share data)</td><td></td><td>2024</td><td></td><td>2023</td></tr><tr><td>ASSETS</td><td>... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "2"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "—"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "2"
},
{
"datatype": "monetaryItemT... |
593 | 593 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "266", "datatype": "monetaryItemType"}, {"numeric_entity": "9.9", "datatype": "percentItemType"}, {"numeric_entity": "10.25", "datatype": "percentItemType"}, {"numeric_entity": "160", "datatype": "monetaryItemType"}, {"numeric_entity": "106", "datatype": "monetaryItemType"}, {"numeric_entity": "114"... | DTE Gas filed a rate case with the MPSC on January 8, 2024 requesting an increase in base rates of $ 266 million based on a projected twelve-month period ending September 30, 2025, and an increase in return on equity from 9.9 % to 10.25 %. The request reflected a net increase to customer rates of only $ 160 million, a... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "266"
},
{
"datatype": "percentItemType",
"numeric_entity": "9.9"
},
{
"datatype": "percentItemType",
"numeric_entity": "10.25"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "160"
},
{
"datatype": "monet... |
597 | 597 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "25900", "datatype": "sharesItemType"}, {"numeric_entity": "12300", "datatype": "sharesItemType"}, {"numeric_entity": "0.8", "datatype": "monetaryItemType"}] | There were approximately 25,900 restricted stock units granted in January 2025 for the vesting period ending in 2027. The grant date fair value of the restricted stock units granted was $ 1.7 million. There were approximately 12,300 restricted stock units awarded in February 2025. The grant date fair value of the share... | [
{
"datatype": "sharesItemType",
"numeric_entity": "25900"
},
{
"datatype": "sharesItemType",
"numeric_entity": "12300"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "0.8"
}
] |
603 | 603 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "1.5", "datatype": "sharesItemType"}, {"numeric_entity": "100000", "datatype": "perShareItemType"}, {"numeric_entity": "1000", "datatype": "perShareItemType"}, {"numeric_entity": "1.5", "datatype": "monetaryItemType"}] | On January 31, 2024, we issued 1.5 million depositary shares, each representing a 1/100th ownership interest in a share of fixed rate reset, non-cumulative perpetual preferred stock, Series I, without par value per share, with a liquidation preference of $ 100,000 per share (equivalent to $ 1,000 per depositary share),... | [
{
"datatype": "sharesItemType",
"numeric_entity": "1.5"
},
{
"datatype": "perShareItemType",
"numeric_entity": "100000"
},
{
"datatype": "perShareItemType",
"numeric_entity": "1000"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1.5"
}
] |
615 | 615 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "142", "datatype": "monetaryItemType"}] | DTE Electric has a pre-tax federal net operating loss carryforward of $ 142 million as of December 31, 2024 which can be carried forward indefinitely. No valuation allowance is required for the federal net operating loss deferred tax asset. | [
{
"datatype": "monetaryItemType",
"numeric_entity": "142"
}
] |
627 | 627 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "153784", "datatype": "sharesItemType"}, {"numeric_entity": "53.26", "datatype": "perShareItemType"}, {"numeric_entity": "150704", "datatype": "sharesItemType"}, {"numeric_entity": "41.13", "datatype": "perShareItemType"}, {"numeric_entity": "60830", "datatype": "sharesItemType"}, {"numeric_entity":... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Performance Unit Awards</td></tr><tr><td></td><td>Shares</td><td></td><td>Weighted-Average Grant-Date Fair Value</td></tr><tr><td>Beginning nonvested grants</td><td>153,784</td><t... | [
{
"datatype": "sharesItemType",
"numeric_entity": "153784"
},
{
"datatype": "perShareItemType",
"numeric_entity": "53.26"
},
{
"datatype": "sharesItemType",
"numeric_entity": "150704"
},
{
"datatype": "perShareItemType",
"numeric_entity": "41.13"
},
{
"datatype": ... |
633 | 633 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "306", "datatype": "monetaryItemType"}] | The Company has uncollateralized letters of credit with an aggregate limit of $ 306 million at December 31, 2024, including $ 260 million that provides a portion of the capital needed to support the Company’s obligations at Lloyd’s. | [
{
"datatype": "monetaryItemType",
"numeric_entity": "306"
}
] |
634 | 634 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "116.6", "datatype": "monetaryItemType"}, {"numeric_entity": "73.5", "datatype": "monetaryItemType"}, {"numeric_entity": "75.7", "datatype": "monetaryItemType"}] | Amortization expense associated with these definite-lived intangible assets was $ 116.6 million, $ 73.5 million and $ 75.7 million in 2024, 2023 and 2022, respectively | [
{
"datatype": "monetaryItemType",
"numeric_entity": "116.6"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "73.5"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "75.7"
}
] |
637 | 637 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "960033", "datatype": "monetaryItemType"}, {"numeric_entity": "343099", "datatype": "monetaryItemType"}, {"numeric_entity": "616934", "datatype": "monetaryItemType"}, {"numeric_entity": "806257", "datatype": "monetaryItemType"}, {"numeric_entity": "606192", "datatype": "monetaryItemType"}, {"numeric... | <table><tr><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td></tr><tr><td> </td><td></td><td>Gross</td><td></td><td> </td><td> </td><td></td><td>Accumulated... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "960033"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "343099"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "616934"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "806257"
},
{
"datat... |
641 | 641 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "149", "datatype": "monetaryItemType"}, {"numeric_entity": "151", "datatype": "monetaryItemType"}, {"numeric_entity": "160", "datatype": "monetaryItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>Year Ended December 31,</td></tr><tr><td>(in millions) (in millions)</td><td></td><td>202... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "149"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "151"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "160"
}
] |
645 | 645 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "1.4", "datatype": "monetaryItemType"}, {"numeric_entity": "1.0", "datatype": "monetaryItemType"}, {"numeric_entity": "2.8", "datatype": "monetaryItemType"}, {"numeric_entity": "3.0", "datatype": "monetaryItemType"}, {"numeric_entity": "9.6", "datatype": "monetaryItemType"}, {"numeric_entity": "68",... | Cross-currency contracts with notional amounts of C$ 1.4 billion ($ 1.0 billion), € 2.8 billion ($ 3.0 billion), JPY 9.6 billion ($ 68 million), and CNY 2.5 billion ($ 344 million). | [
{
"datatype": "monetaryItemType",
"numeric_entity": "1.4"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1.0"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "2.8"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "3.0"
},
{
"datatype": "monet... |
658 | 658 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "50.0", "datatype": "monetaryItemType"}, {"numeric_entity": "11", "datatype": "percentItemType"}, {"numeric_entity": "47.1", "datatype": "monetaryItemType"}] | In December 2023, the Company entered into a $ 50.0 million secured term loan with a principal of an operator that bears interest at a fixed rate of 11 % per annum and matures on December 19, 2026 . In connection with entering into this loan, we also entered into two lease amendments to extend the term of two leases wi... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "50.0"
},
{
"datatype": "percentItemType",
"numeric_entity": "11"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "47.1"
}
] |
663 | 663 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "500000", "datatype": "monetaryItemType"}, {"numeric_entity": "3.05", "datatype": "percentItemType"}, {"numeric_entity": "5682", "datatype": "monetaryItemType"}, {"numeric_entity": "100", "datatype": "percentItemType"}] | On March 13, 2020, the Company completed an underwritten public offering of $ 500,000 aggregate principal amount of 3.05 % Senior Notes due April 1, 2050 (the “2050 Senior Notes”). The 2050 Senior Notes were issued under the Indenture, as supplemented through the Fourth Supplemental Indenture, dated as of March 13, 202... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "500000"
},
{
"datatype": "percentItemType",
"numeric_entity": "3.05"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "5682"
},
{
"datatype": "percentItemType",
"numeric_entity": "100"
}
] |
667 | 667 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "11394", "datatype": "monetaryItemType"}, {"numeric_entity": "76", "datatype": "monetaryItemType"}, {"numeric_entity": "7356", "datatype": "monetaryItemType"}, {"numeric_entity": "276", "datatype": "monetaryItemType"}, {"numeric_entity": "297", "datatype": "monetaryItemType"}, {"numeric_entity": "28... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>December 31, 2024</td><td></td><td>... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "11394"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "76"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "7356"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "276"
},
{
"datatype": "mon... |
669 | 669 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "1373", "datatype": "monetaryItemType"}, {"numeric_entity": "1358", "datatype": "monetaryItemType"}, {"numeric_entity": "1091", "datatype": "monetaryItemType"}, {"numeric_entity": "1373", "datatype": "monetaryItemType"}, {"numeric_entity": "1358", "datatype": "monetaryItemType"}, {"numeric_entity": ... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td>Year Ended December 31,</td></tr><tr><td>(in millions)</td><td></td><td>2024</td><td></td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "1373"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1358"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1091"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1373"
},
{
"datatype": "m... |
673 | 673 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "2299", "datatype": "monetaryItemType"}, {"numeric_entity": "1958", "datatype": "monetaryItemType"}, {"numeric_entity": "2215", "datatype": "monetaryItemType"}, {"numeric_entity": "55", "datatype": "monetaryItemType"}, {"numeric_entity": "15", "datatype": "monetaryItemType"}, {"numeric_entity": "39"... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Year ended December 31,</td></tr><tr><td></td><td>2024</td><td></td><td>2023</td><td></td><td>2022</td></tr><tr><td>Net incom... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "2299"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1958"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "2215"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "55"
},
{
"datatype": "mon... |
681 | 681 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "173", "datatype": "monetaryItemType"}, {"numeric_entity": "173", "datatype": "monetaryItemType"}, {"numeric_entity": "375", "datatype": "monetaryItemType"}, {"numeric_entity": "355", "datatype": "monetaryItemType"}, {"numeric_entity": "50", "datatype": "sharesItemType"}, {"numeric_entity": "57", "d... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Year Ended December 31,</td></tr><tr><td>(in millions, except per share data)</td><td>2024</td><td>2023</td><td>2022</td></tr><tr><td>Net income</td><td>$</td><td>173 </td><td></t... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "173"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "173"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "375"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "355"
},
{
"datatype": "share... |
689 | 689 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "94", "datatype": "monetaryItemType"}] | The cash flows associated with derivatives designated as net investment hedges are recorded in All other investing activities – net in the Consolidated and Combined Statements of Cash Flows. For the year ended December 31, 2024, All other investing activities – net includes a $ 94 million payment for the settlement of ... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "94"
}
] |
692 | 692 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "32", "datatype": "monetaryItemType"}, {"numeric_entity": "17", "datatype": "monetaryItemType"}, {"numeric_entity": "6", "datatype": "monetaryItemType"}, {"numeric_entity": "39", "datatype": "monetaryItemType"}, {"numeric_entity": "2", "datatype": "monetaryItemType"}, {"numeric_entity": "1", "dataty... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Millions of dollars</td><td></td><td>United States Pension Benefits</td><td></td><td>Foreign Pension Benefi... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "32"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "17"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "6"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "39"
},
{
"datatype": "monetaryIt... |
693 | 693 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "213", "datatype": "monetaryItemType"}, {"numeric_entity": "50", "datatype": "monetaryItemType"}, {"numeric_entity": "16", "datatype": "monetaryItemType"}, {"numeric_entity": "25", "datatype": "monetaryItemType"}, {"numeric_entity": "122", "datatype": "monetaryItemType"}, {"numeric_entity": "5", "da... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "213"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "50"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "16"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "25"
},
{
"datatype": "monetary... |
707 | 707 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "5.25", "datatype": "percentItemType"}, {"numeric_entity": "5.50", "datatype": "percentItemType"}, {"numeric_entity": "4.18", "datatype": "percentItemType"}] | Includes 5.25 %, 5.50 % and 4.18 % for the U.K. pension plans for December 31, 2024, 2023 and 2022, respectively. | [
{
"datatype": "percentItemType",
"numeric_entity": "5.25"
},
{
"datatype": "percentItemType",
"numeric_entity": "5.50"
},
{
"datatype": "percentItemType",
"numeric_entity": "4.18"
}
] |
714 | 714 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "3452", "datatype": "monetaryItemType"}, {"numeric_entity": "3008", "datatype": "monetaryItemType"}, {"numeric_entity": "1851", "datatype": "monetaryItemType"}, {"numeric_entity": "8311", "datatype": "monetaryItemType"}, {"numeric_entity": "1", "datatype": "monetaryItemType"}, {"numeric_entity": "83... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Kentucky Regulated</td><td></td><td>Pennsylvania Regulated</td><td></td... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "3452"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "3008"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "1851"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "8311"
},
{
"datatype": "m... |
717 | 717 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "65", "datatype": "monetaryItemType"}, {"numeric_entity": "120", "datatype": "monetaryItemType"}] | In 2015, the EPA published a final rule (2015 Rule) regulating CCR as nonhazardous waste under Subtitle D of the Resource Conservation and Recovery Act (RCRA) in the Federal Register. The rule included additional requirements for new landfill and impoundment construction as well as closure activities related to certain... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "65"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "120"
}
] |
721 | 721 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "43160", "datatype": "monetaryItemType"}, {"numeric_entity": "12973", "datatype": "monetaryItemType"}, {"numeric_entity": "30187", "datatype": "monetaryItemType"}, {"numeric_entity": "600", "datatype": "monetaryItemType"}, {"numeric_entity": "467", "datatype": "monetaryItemType"}, {"numeric_entity":... | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>December 31, 2023</td></tr><tr><td></td><td>Gross carrying value</td><t... | [
{
"datatype": "monetaryItemType",
"numeric_entity": "43160"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "12973"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "30187"
},
{
"datatype": "monetaryItemType",
"numeric_entity": "600"
},
{
"datatype": ... |
734 | 734 | train | <role>
You are an expert financial table tagging analyst.
</role>
<task>
Extract numeric entity and datatype pairs from the provided financial text/table.
Input: one financial text or HTML table.
Output: a JSON array. Each array item must contain exactly:
- "numeric_entity": the normalized numeric value string
- "dat... | [{"numeric_entity": "1284", "datatype": "sharesItemType"}] | <table><tr><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Common Stock</td></tr><tr><td></td></tr><tr><td>Future grant of stock-based compensation</td><td>1,162</td><td></td></tr><tr><td>Shares reserved under other equity compensation plans</td><td>122</td><td></td></tr><tr><td>TOTAL</td><t... | [
{
"datatype": "sharesItemType",
"numeric_entity": "1284"
}
] |
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