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causal20sc200 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Below we can see TII's EPS growth has grown in step with the portfolio build-up and a tight control on overhead. The company began reporting a provision for credit loss in 2015 which is why diluted EPS hasn't reached it's 2015 levels.
Answer: | noise | Below we can see TII's EPS growth has grown in step with the portfolio build-up and a tight control on overhead. The company began reporting a provision for credit loss in 2015 which is why diluted EPS hasn't reached it's 2015 levels. | [
"noise",
"causal"
] | 0 |
causal20sc201 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The company has been able to not only constantly grow book value and book value per share (21% CAGR since 2013), but has also raised equity at increasing per-share prices, and has either grown organically into or issued equity at prices that surpassed the previous book value per share peak. Below is a list of equity raises: Q210: $8.0 MM shares issued at 0.30/share.
Answer: | noise | The company has been able to not only constantly grow book value and book value per share (21% CAGR since 2013), but has also raised equity at increasing per-share prices, and has either grown organically into or issued equity at prices that surpassed the previous book value per share peak. Below is a list of equity raises: Q210: $8.0 MM shares issued at 0.30/share. | [
"noise",
"causal"
] | 0 |
causal20sc202 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Q411: $11.7M shares issued at $0.50/share.
Answer: | noise | Q411: $11.7M shares issued at $0.50/share. | [
"noise",
"causal"
] | 0 |
causal20sc203 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Q414: $10.6M shares issued at $0.63/share.
Answer: | noise | Q414: $10.6M shares issued at $0.63/share. | [
"noise",
"causal"
] | 0 |
causal20sc204 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Q415: $18.1M shares issued at $0.85/share.
Answer: | noise | Q415: $18.1M shares issued at $0.85/share. | [
"noise",
"causal"
] | 0 |
causal20sc205 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: In August 2018 TII announced the closing of a $20 Million US credit facility with Texas Capital. TII formed a new wholly owned subsidiary, TFCC USA LLC (TFCC USA) with the purpose of holding US loans and investments. The credit facility will be secured by loans and investments held in TFCC USA.
Answer: | noise | In August 2018 TII announced the closing of a $20 Million US credit facility with Texas Capital. TII formed a new wholly owned subsidiary, TFCC USA LLC (TFCC USA) with the purpose of holding US loans and investments. The credit facility will be secured by loans and investments held in TFCC USA. | [
"noise",
"causal"
] | 0 |
causal20sc206 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The credit facility has since been expanded to $35 Million U.S. TII has also raised over $420M in third party capital from HNW individuals, which should aid in managements goal of deploying $135 Million Canadian in capital in 2019. Data by YCharts As we can see the stock hasn't traded at a premium to BV that often since its IPO in 2007, only really between about 2014 FYE to about 2016 FYE. Since 2016 FYE the discount to BV has widened. Most mortgage REITs which are a similar business model trade at at least 1:1 with BV.
Answer: | noise | The credit facility has since been expanded to $35 Million U.S. TII has also raised over $420M in third party capital from HNW individuals, which should aid in managements goal of deploying $135 Million Canadian in capital in 2019. Data by YCharts As we can see the stock hasn't traded at a premium to BV that often since its IPO in 2007, only really between about 2014 FYE to about 2016 FYE. Since 2016 FYE the discount to BV has widened. Most mortgage REITs which are a similar business model trade at at least 1:1 with BV. | [
"noise",
"causal"
] | 0 |
causal20sc207 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Goeasy Ltd. provides loans and other financial services to consumers in Canada, it also leases household products to consumers, and does even higher risk loans and trades at 2.5x BV. The stock has been held back by the bad performance of the Canadian markets as a whole.
Answer: | noise | Goeasy Ltd. provides loans and other financial services to consumers in Canada, it also leases household products to consumers, and does even higher risk loans and trades at 2.5x BV. The stock has been held back by the bad performance of the Canadian markets as a whole. | [
"noise",
"causal"
] | 0 |
causal20sc208 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: I believe that over longer periods of time, stocks will move in relationship with their results. Over shorter periods of time though, a bull or bear market can have a significant influence on the price of this security.
Answer: | noise | I believe that over longer periods of time, stocks will move in relationship with their results. Over shorter periods of time though, a bull or bear market can have a significant influence on the price of this security. | [
"noise",
"causal"
] | 0 |
causal20sc209 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Given the current focus and expected pace of growth over the next few years, I expect the market to start rewarding the company for strong execution. TII announced in June 2019 that they will be initiating a quarterly dividend program starting in the third quarter of the 2019 fiscal year.
Answer: | noise | Given the current focus and expected pace of growth over the next few years, I expect the market to start rewarding the company for strong execution. TII announced in June 2019 that they will be initiating a quarterly dividend program starting in the third quarter of the 2019 fiscal year. | [
"noise",
"causal"
] | 0 |
causal20sc210 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The board of directors has declared an initial cash dividend of $0.005 per common share for the third quarter of 2019 (subject to adjustment in the event of any share consolidation which may occur prior to the payment thereof).
Answer: | noise | The board of directors has declared an initial cash dividend of $0.005 per common share for the third quarter of 2019 (subject to adjustment in the event of any share consolidation which may occur prior to the payment thereof). | [
"noise",
"causal"
] | 0 |
causal20sc211 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: This will work out to a yield of ~4%.
Answer: | noise | This will work out to a yield of ~4%. | [
"noise",
"causal"
] | 0 |
causal20sc212 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Given the YoY increase in BV, there is no reason to believe that this dividend won't increase YoY going forward.
Answer: | noise | Given the YoY increase in BV, there is no reason to believe that this dividend won't increase YoY going forward. | [
"noise",
"causal"
] | 0 |
causal20sc213 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Given that TII is prepared to advance funds up to a LTV of 80%, TII will likely be negatively affected if real estate markets in any of its target regions see a rapid decrease in property value which prevents repayment of the outstanding loans. TII mitigates some of this risk by loaning money to borrowers that are developing infill type opportunities in established metropolitan areas. The company also typically keeps the duration of loans relatively short so the term doesn't exceed the typical real estate cycles.
Answer: | noise | Given that TII is prepared to advance funds up to a LTV of 80%, TII will likely be negatively affected if real estate markets in any of its target regions see a rapid decrease in property value which prevents repayment of the outstanding loans. TII mitigates some of this risk by loaning money to borrowers that are developing infill type opportunities in established metropolitan areas. The company also typically keeps the duration of loans relatively short so the term doesn't exceed the typical real estate cycles. | [
"noise",
"causal"
] | 0 |
causal20sc214 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The weighted average life of the company's loan portfolio at December 31, 2018 and 2017 was 1.67 years and 1.85 years respectively. TII's real driver of value creation is syndication.
Answer: | noise | The weighted average life of the company's loan portfolio at December 31, 2018 and 2017 was 1.67 years and 1.85 years respectively. TII's real driver of value creation is syndication. | [
"noise",
"causal"
] | 0 |
causal20sc215 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The ability to tap this source of lending could be materially impacted should the company have any major loan defaults. As the speed of the company's top line growth is dictated in part by the speed of capital deployment, there is a balancing act between loan origination vs. the amount of due diligence performed. If borrowers fail to make payments, the company may have to rely on term extensions or to collect on its security (the value of which may be impaired parallel to the overall market).
Answer: | noise | The ability to tap this source of lending could be materially impacted should the company have any major loan defaults. As the speed of the company's top line growth is dictated in part by the speed of capital deployment, there is a balancing act between loan origination vs. the amount of due diligence performed. If borrowers fail to make payments, the company may have to rely on term extensions or to collect on its security (the value of which may be impaired parallel to the overall market). | [
"noise",
"causal"
] | 0 |
causal20sc216 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Furthermore, even if the company is able to recover its principal and legal fees in its entirety, this will still put a dent in IRR for equity holders. I firmly believe that this stock is greatly undervalued given TII's ability to leverage its existing equity to obtain strong IRRs on its investments. Which is why I believe the stock should trade at at least 1:1 with BV/share which would mean an $0.80/share target and 60% upside from the current $0.50/share price.
Answer: | noise | Furthermore, even if the company is able to recover its principal and legal fees in its entirety, this will still put a dent in IRR for equity holders. I firmly believe that this stock is greatly undervalued given TII's ability to leverage its existing equity to obtain strong IRRs on its investments. Which is why I believe the stock should trade at at least 1:1 with BV/share which would mean an $0.80/share target and 60% upside from the current $0.50/share price. | [
"noise",
"causal"
] | 0 |
causal20sc217 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.
Answer: | noise | Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. | [
"noise",
"causal"
] | 0 |
causal20sc218 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: I wrote this article myself, and it expresses my own opinions.
Answer: | noise | I wrote this article myself, and it expresses my own opinions. | [
"noise",
"causal"
] | 0 |
causal20sc219 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: I am not receiving compensation for it (other than from Seeking Alpha).
Answer: | noise | I am not receiving compensation for it (other than from Seeking Alpha). | [
"noise",
"causal"
] | 0 |
causal20sc220 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: I have no business relationship with any company whose stock is mentioned in this article. Brant Munro CFA Value, growth at reasonable price, long-term horizon, event-driven
Answer: | noise | I have no business relationship with any company whose stock is mentioned in this article. Brant Munro CFA Value, growth at reasonable price, long-term horizon, event-driven | [
"noise",
"causal"
] | 0 |
causal20sc221 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Banerjee also told reporters said that she had sought time from Shah, insisting that it was part of her routine exercise as chief minister to meet the union finance and home ministers during her trips to Delhi.
Answer: | noise | Banerjee also told reporters said that she had sought time from Shah, insisting that it was part of her routine exercise as chief minister to meet the union finance and home ministers during her trips to Delhi. | [
"noise",
"causal"
] | 0 |
causal20sc222 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: (ANI photo) TMC chief Mamata Banerjee will call on Home Minister Amit Shah on Thursday, leading to speculation that the meeting is an effort to rescue former Kolkata police commissioner Rajeev Kumar who is under the CBI's scanner and is believed to be close to her, sources said.
Answer: | noise | (ANI photo) TMC chief Mamata Banerjee will call on Home Minister Amit Shah on Thursday, leading to speculation that the meeting is an effort to rescue former Kolkata police commissioner Rajeev Kumar who is under the CBI's scanner and is believed to be close to her, sources said. | [
"noise",
"causal"
] | 0 |
causal20sc223 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The West Bengal chief minister, who is on a three-day visit to the national capital, met Prime Minister Narendra Modi on Wednesday. She described it as a government to government meeting and said the discussion was mostly on development issues of the state.
Answer: | noise | The West Bengal chief minister, who is on a three-day visit to the national capital, met Prime Minister Narendra Modi on Wednesday. She described it as a government to government meeting and said the discussion was mostly on development issues of the state. | [
"noise",
"causal"
] | 0 |
causal20sc224 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Banerjee also told reporters said that she had sought time from Shah, insisting that it was part of her routine exercise as chief minister to meet the union finance and home ministers during her trips to Delhi.
Answer: | noise | Banerjee also told reporters said that she had sought time from Shah, insisting that it was part of her routine exercise as chief minister to meet the union finance and home ministers during her trips to Delhi. | [
"noise",
"causal"
] | 0 |
causal20sc225 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: She said she will not have time to meet the finance minister but will meet the home minister. Also read| Thinking ahead: BJP banks on younger leaders for crucial roles with eye on future West Bengal BJP chief Dilip Ghosh told reporters in Bengal on Wednesday that he was happy that Banerjee's good sense had prevailed that she met the prime minister.
Answer: | noise | She said she will not have time to meet the finance minister but will meet the home minister. Also read| Thinking ahead: BJP banks on younger leaders for crucial roles with eye on future West Bengal BJP chief Dilip Ghosh told reporters in Bengal on Wednesday that he was happy that Banerjee's good sense had prevailed that she met the prime minister. | [
"noise",
"causal"
] | 0 |
causal20sc226 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: But I think it's too late.
Answer: | noise | But I think it's too late. | [
"noise",
"causal"
] | 0 |
causal20sc227 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Her attempts to save herself and her party from CBI will not yield any results, he said. Several TMC leaders and former Kolkata police chief Rajeev Kumar have come under the CBI scanner in connection with a ponzi scam related to the Saradha group. The Saradha group of companies allegedly duped lakhs of people of Rs 2,500 crore, promising higher rates of return on their investments.
Answer: | noise | Her attempts to save herself and her party from CBI will not yield any results, he said. Several TMC leaders and former Kolkata police chief Rajeev Kumar have come under the CBI scanner in connection with a ponzi scam related to the Saradha group. The Saradha group of companies allegedly duped lakhs of people of Rs 2,500 crore, promising higher rates of return on their investments. | [
"noise",
"causal"
] | 0 |
causal20sc228 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Assembly polls in Bengal are due in April-May 2021.
Answer: | noise | Assembly polls in Bengal are due in April-May 2021. | [
"noise",
"causal"
] | 0 |
causal20sc229 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Wilmington sees 10% drop in FY Ebitda but 'promising' sales in new year StockMarketWire.com - Information and education provider Wilmington reported a 9.7% drop in full-year earnings, reflecting previously announced cost increases to support its growth, even as it saw a 1% increase in revenues. Adjusted Ebitda fell 9.7% to £21.5m with Ebita margins at 17.6% while adjusted pre-tax profit fell 11.5% to £19.3m for the 12 months to 30 June 2019.
Answer: | causal | Wilmington sees 10% drop in FY Ebitda but 'promising' sales in new year StockMarketWire.com - Information and education provider Wilmington reported a 9.7% drop in full-year earnings, reflecting previously announced cost increases to support its growth, even as it saw a 1% increase in revenues. Adjusted Ebitda fell 9.7% to £21.5m with Ebita margins at 17.6% while adjusted pre-tax profit fell 11.5% to £19.3m for the 12 months to 30 June 2019. | [
"noise",
"causal"
] | 1 |
causal20sc230 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: However, revenue rose 1% to £122.5m. This was driven by double-digit growth in the firm's compliance business, while the healthcare division recovered from a 'challenging' year to achieve 1% growth.
Answer: | causal | However, revenue rose 1% to £122.5m. This was driven by double-digit growth in the firm's compliance business, while the healthcare division recovered from a 'challenging' year to achieve 1% growth. | [
"noise",
"causal"
] | 1 |
causal20sc231 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Trading in the first two months of the new year had been in line with board expectations with revenue growth compared with the previous year and 'promising' sales performance across all three divisions. The company said it expected to see full-year organic revenue growth in the low to mid single-digit range.
Answer: | noise | Trading in the first two months of the new year had been in line with board expectations with revenue growth compared with the previous year and 'promising' sales performance across all three divisions. The company said it expected to see full-year organic revenue growth in the low to mid single-digit range. | [
"noise",
"causal"
] | 0 |
causal20sc232 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: 'Wilmington made progress over the year on our objective of focussing the group on delivering organic growth.
Answer: | noise | 'Wilmington made progress over the year on our objective of focussing the group on delivering organic growth. | [
"noise",
"causal"
] | 0 |
causal20sc233 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: We built momentum despite having to deal with the current uncertainties in the political and economic climate. The board maintains its view that the group is well positioned to build on this and deliver improved performance and increased shareholder value,' said non-executive chairman Martin Morgan. Wilmington said it would pay a final dividend of 5p, up 4% on the previous year, with total dividends of 9.1p (up 3% year on year).
Answer: | causal | We built momentum despite having to deal with the current uncertainties in the political and economic climate. The board maintains its view that the group is well positioned to build on this and deliver improved performance and increased shareholder value,' said non-executive chairman Martin Morgan. Wilmington said it would pay a final dividend of 5p, up 4% on the previous year, with total dividends of 9.1p (up 3% year on year). | [
"noise",
"causal"
] | 1 |
causal20sc234 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Section | Table of Contents By: Christopher Caldwell Posted: April 30, 2019 This article appeared in: Volume XIX, Number 2, Spring 2019 o English-language newspaper reported on it at the time, nor has any cited it since, but the speech Hungarian prime minister Viktor Orbán made before an annual picnic for his party's intellectual leaders in the late summer of 2015 is probably the most important by a Western statesman this century.
Answer: | noise | Section | Table of Contents By: Christopher Caldwell Posted: April 30, 2019 This article appeared in: Volume XIX, Number 2, Spring 2019 o English-language newspaper reported on it at the time, nor has any cited it since, but the speech Hungarian prime minister Viktor Orbán made before an annual picnic for his party's intellectual leaders in the late summer of 2015 is probably the most important by a Western statesman this century. | [
"noise",
"causal"
] | 0 |
causal20sc235 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: As Orbán spoke in the village of Kötcse, by Lake Balaton, hundreds of thousands of migrants from across the Muslim world, most of them young men, were marching northwestwards out of Asia Minor, across the Balkan countries and into the heart of Europe. Already, mobs of migrants had broken Hungarian police lines, trampled cropland, occupied town squares, shut down highways, stormed trains, and massed in front of Budapest's Keleti train station. German chancellor Angela Merkel had invited those fleeing the Syrian civil war to seek refuge in Europe.
Answer: | noise | As Orbán spoke in the village of Kötcse, by Lake Balaton, hundreds of thousands of migrants from across the Muslim world, most of them young men, were marching northwestwards out of Asia Minor, across the Balkan countries and into the heart of Europe. Already, mobs of migrants had broken Hungarian police lines, trampled cropland, occupied town squares, shut down highways, stormed trains, and massed in front of Budapest's Keleti train station. German chancellor Angela Merkel had invited those fleeing the Syrian civil war to seek refuge in Europe. | [
"noise",
"causal"
] | 0 |
causal20sc236 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: They had been joined en route, in at least equal number, by migrants from Iraq, Iran, Pakistan, Bangladesh, Afghanistan, and elsewhere. For Hungarians, this was playing with fire.
Answer: | noise | They had been joined en route, in at least equal number, by migrants from Iraq, Iran, Pakistan, Bangladesh, Afghanistan, and elsewhere. For Hungarians, this was playing with fire. | [
"noise",
"causal"
] | 0 |
causal20sc237 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: They are taught in school to think of their Magyar ancestors as having ridden off the Asian steppes to put much of Europe to the torch (Attila is a popular boys' name), and they themselves suffered centuries of subjugation under the Ottomans, who marched north on the same roads the Syrian refugees used in the internet age. But no one was supposed to bring up the past. Merkel and her defenders had raised the subject of human rights, which until then had been sufficient to stifle misgivings.
Answer: | noise | They are taught in school to think of their Magyar ancestors as having ridden off the Asian steppes to put much of Europe to the torch (Attila is a popular boys' name), and they themselves suffered centuries of subjugation under the Ottomans, who marched north on the same roads the Syrian refugees used in the internet age. But no one was supposed to bring up the past. Merkel and her defenders had raised the subject of human rights, which until then had been sufficient to stifle misgivings. | [
"noise",
"causal"
] | 0 |
causal20sc238 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: In Kötcse, Orbán informed Merkel and the world that it no longer was. Orbán was preparing a military closure of his country's southern border.
Answer: | noise | In Kötcse, Orbán informed Merkel and the world that it no longer was. Orbán was preparing a military closure of his country's southern border. | [
"noise",
"causal"
] | 0 |
causal20sc239 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: That Europe's ancient nation-states would serve in this way as the first line of defense for the continent's external borders, such as the one between Hungary and Serbia, was exactly what had been assumed two decades before in the founding treaties of the European Union, the 28-nation federation-in-embryo centered in Brussels and dominated by Merkel's Germany.
Answer: | noise | That Europe's ancient nation-states would serve in this way as the first line of defense for the continent's external borders, such as the one between Hungary and Serbia, was exactly what had been assumed two decades before in the founding treaties of the European Union, the 28-nation federation-in-embryo centered in Brussels and dominated by Merkel's Germany. | [
"noise",
"causal"
] | 0 |
causal20sc240 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: But sometime after Hungary joined the E.U. in 2004, this question of Europe's borders had become complicated, legalistic, and obscured by what Orbán called liberal babble. Orbán now had to make a philosophical argument for why he should not be evicted from civilized company for carrying out what a decade before would have been considered the most basic part of his job.
Answer: | noise | But sometime after Hungary joined the E.U. in 2004, this question of Europe's borders had become complicated, legalistic, and obscured by what Orbán called liberal babble. Orbán now had to make a philosophical argument for why he should not be evicted from civilized company for carrying out what a decade before would have been considered the most basic part of his job. | [
"noise",
"causal"
] | 0 |
causal20sc241 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: His Fidesz party had always belonged to the same political family that Merkel's did - the hodgepodge of postwar conservative parties called Christian Democracy.
Answer: | noise | His Fidesz party had always belonged to the same political family that Merkel's did - the hodgepodge of postwar conservative parties called Christian Democracy. | [
"noise",
"causal"
] | 0 |
causal20sc242 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Now, as Orbán spoke, it was clear the two were arguing from different centuries, opposite ideologies, and irreconcilable Europes.
Answer: | noise | Now, as Orbán spoke, it was clear the two were arguing from different centuries, opposite ideologies, and irreconcilable Europes. | [
"noise",
"causal"
] | 0 |
causal20sc243 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Hungary must protect its ethnic and cultural composition, he said at Kötcse (which more or less rhymes with butcher).
Answer: | noise | Hungary must protect its ethnic and cultural composition, he said at Kötcse (which more or less rhymes with butcher). | [
"noise",
"causal"
] | 0 |
causal20sc244 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: I am convinced that Hungary has the right - and every nation has the right - to say that it does not want its country to change. France and Britain had been perfectly within their prerogatives to admit millions of immigrants from the former Third World.
Answer: | noise | I am convinced that Hungary has the right - and every nation has the right - to say that it does not want its country to change. France and Britain had been perfectly within their prerogatives to admit millions of immigrants from the former Third World. | [
"noise",
"causal"
] | 0 |
causal20sc245 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Germany was entitled to welcome as many Turks as it liked. I think they had a right to make this decision, Orbán said.
Answer: | noise | Germany was entitled to welcome as many Turks as it liked. I think they had a right to make this decision, Orbán said. | [
"noise",
"causal"
] | 0 |
causal20sc246 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: We have a duty to look at where this has taken them.
Answer: | noise | We have a duty to look at where this has taken them. | [
"noise",
"causal"
] | 0 |
causal20sc247 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: He did not care to repeat the experiment.
Answer: | noise | He did not care to repeat the experiment. | [
"noise",
"causal"
] | 0 |
causal20sc248 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Migrants kept coming, and the European mood shifted.
Answer: | noise | Migrants kept coming, and the European mood shifted. | [
"noise",
"causal"
] | 0 |
causal20sc249 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: In Germany, Alternative for Germany (AfD), a party founded by economists to protest European Union currency policy, shifted its attention to migration and began to harvest double-digit election returns in one German state after another.
Answer: | noise | In Germany, Alternative for Germany (AfD), a party founded by economists to protest European Union currency policy, shifted its attention to migration and began to harvest double-digit election returns in one German state after another. | [
"noise",
"causal"
] | 0 |
causal20sc250 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The Polish government fell after approving a plan to redistribute into eastern Europe the migrants Merkel had welcomed. But if any European politician symbolized this reassessment, it was Orbán. Signs appeared at rallies in Germany reading Orban, Help Us!
Answer: | noise | The Polish government fell after approving a plan to redistribute into eastern Europe the migrants Merkel had welcomed. But if any European politician symbolized this reassessment, it was Orbán. Signs appeared at rallies in Germany reading Orban, Help Us! | [
"noise",
"causal"
] | 0 |
causal20sc251 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: His dissent split Europeans into two clashing ideologies. With the approach in May 2019 of elections to the European Union parliament, the first since the migrant crisis, Europeans were being offered a stark choice between two irreconcilable societies: Orbán's nationalism, which commands the assent of popular majorities, and Merkel's human rights, a continuation of projects E.U. leaders had tried to carry out in the past quarter-century.
Answer: | noise | His dissent split Europeans into two clashing ideologies. With the approach in May 2019 of elections to the European Union parliament, the first since the migrant crisis, Europeans were being offered a stark choice between two irreconcilable societies: Orbán's nationalism, which commands the assent of popular majorities, and Merkel's human rights, a continuation of projects E.U. leaders had tried to carry out in the past quarter-century. | [
"noise",
"causal"
] | 0 |
causal20sc252 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: One of these will be the Europe of tomorrow.
Answer: | noise | One of these will be the Europe of tomorrow. | [
"noise",
"causal"
] | 0 |
causal20sc253 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Versailles, Moscow, Brussels Orbán is more than the bohunk version of Donald Trump that he is often portrayed as.
Answer: | noise | Versailles, Moscow, Brussels Orbán is more than the bohunk version of Donald Trump that he is often portrayed as. | [
"noise",
"causal"
] | 0 |
causal20sc254 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: He is blessed with almost every political gift - brave, shrewd with his enemies and trustworthy with his friends, detail-oriented, hilarious.
Answer: | noise | He is blessed with almost every political gift - brave, shrewd with his enemies and trustworthy with his friends, detail-oriented, hilarious. | [
"noise",
"causal"
] | 0 |
causal20sc255 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: In the last years of the Cold War, he stuck his neck out further than any young dissident in assailing the Soviet Union. That courage helped land him in the prime minister's office for the first time in 1998, at age 35.
Answer: | noise | In the last years of the Cold War, he stuck his neck out further than any young dissident in assailing the Soviet Union. That courage helped land him in the prime minister's office for the first time in 1998, at age 35. | [
"noise",
"causal"
] | 0 |
causal20sc256 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: He has a memory for parliamentary minutiae reminiscent of Bill Clinton.
Answer: | noise | He has a memory for parliamentary minutiae reminiscent of Bill Clinton. | [
"noise",
"causal"
] | 0 |
causal20sc257 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: At a January press conference, he interrupted a speechifying reporter by saying, If I've counted correctly, that's six questions, then answered them in sequence with references to historical per capita income shifts, employment rates, demographic projections, and the like. His secret weapon, though, is his intellectual curiosity.
Answer: | noise | At a January press conference, he interrupted a speechifying reporter by saying, If I've counted correctly, that's six questions, then answered them in sequence with references to historical per capita income shifts, employment rates, demographic projections, and the like. His secret weapon, though, is his intellectual curiosity. | [
"noise",
"causal"
] | 0 |
causal20sc258 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: As Irving Kristol did when he edited the Public Interest in the 1980s, Orbán urges his aides to take one day a week off to devote to their reading and writing. He does so himself, clearing his Thursdays when he can.
Answer: | noise | As Irving Kristol did when he edited the Public Interest in the 1980s, Orbán urges his aides to take one day a week off to devote to their reading and writing. He does so himself, clearing his Thursdays when he can. | [
"noise",
"causal"
] | 0 |
causal20sc259 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Raised poor in a small town west of Budapest, preoccupied early by politics, he has had to acquire much of his education on the fly, as a busy adult. His ideas are powerful, raw, and unsettled.
Answer: | noise | Raised poor in a small town west of Budapest, preoccupied early by politics, he has had to acquire much of his education on the fly, as a busy adult. His ideas are powerful, raw, and unsettled. | [
"noise",
"causal"
] | 0 |
causal20sc260 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Orbán has changed his mind about a lot of things - unregulated free markets above all.
Answer: | noise | Orbán has changed his mind about a lot of things - unregulated free markets above all. | [
"noise",
"causal"
] | 0 |
causal20sc261 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Out of a regime of deep reading and disputation come his larger theories about the direction of Western civilization, and many people probably find voting for Orbán satisfying in the way that reading Jared Diamond or Yuval Noah Hariri is satisfying.
Answer: | noise | Out of a regime of deep reading and disputation come his larger theories about the direction of Western civilization, and many people probably find voting for Orbán satisfying in the way that reading Jared Diamond or Yuval Noah Hariri is satisfying. | [
"noise",
"causal"
] | 0 |
causal20sc262 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Orbán believes that Western countries are in decline, and that they are in decline because of liberalism, which in his political vocabulary is a slur.
Answer: | noise | Orbán believes that Western countries are in decline, and that they are in decline because of liberalism, which in his political vocabulary is a slur. | [
"noise",
"causal"
] | 0 |
causal20sc263 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: He uses the word to describe the contemporary process of creating neutral social structures and a level playing field, usually in the name of rights.
Answer: | noise | He uses the word to describe the contemporary process of creating neutral social structures and a level playing field, usually in the name of rights. | [
"noise",
"causal"
] | 0 |
causal20sc264 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: This project of creating neutral institutions has two problems.
Answer: | noise | This project of creating neutral institutions has two problems. | [
"noise",
"causal"
] | 0 |
causal20sc265 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: First, it is destructive, because the bonds of affection out of which communities are built are - by definition - non-neutral. Second, it is a lie, because someone must administer this project, and administration, though advertised as neutral, rarely is.
Answer: | noise | First, it is destructive, because the bonds of affection out of which communities are built are - by definition - non-neutral. Second, it is a lie, because someone must administer this project, and administration, though advertised as neutral, rarely is. | [
"noise",
"causal"
] | 0 |
causal20sc266 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Some must administer over others.
Answer: | noise | Some must administer over others. | [
"noise",
"causal"
] | 0 |
causal20sc267 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Carried to its logical conclusion, liberalism will, in Orbán's view, destroy Hungary.
Answer: | noise | Carried to its logical conclusion, liberalism will, in Orbán's view, destroy Hungary. | [
"noise",
"causal"
] | 0 |
causal20sc268 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: It is not written in the great book of humanity that there must be Hungarians in the world, he said in his State of the Nation address in February. It is only written in our hearts - but the world cares nothing for that.
Answer: | noise | It is not written in the great book of humanity that there must be Hungarians in the world, he said in his State of the Nation address in February. It is only written in our hearts - but the world cares nothing for that. | [
"noise",
"causal"
] | 0 |
causal20sc269 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: This sense that Hungary might be only one political miscalculation away from extinction is widely shared.
Answer: | noise | This sense that Hungary might be only one political miscalculation away from extinction is widely shared. | [
"noise",
"causal"
] | 0 |
causal20sc270 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: There was one country, in the wake of World War I, that was treated more harshly than Germany. The Treaty of Trianon turned a cosmopolitan, advanced central European powerhouse of 20 million people - the Kingdom of Hungary, Budapest's half of the Austro-Hungarian empire - into a statelet of 8 million and divvied up two thirds of its territory among other nations.
Answer: | noise | There was one country, in the wake of World War I, that was treated more harshly than Germany. The Treaty of Trianon turned a cosmopolitan, advanced central European powerhouse of 20 million people - the Kingdom of Hungary, Budapest's half of the Austro-Hungarian empire - into a statelet of 8 million and divvied up two thirds of its territory among other nations. | [
"noise",
"causal"
] | 0 |
causal20sc271 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: This dismemberment helps explain many of the worst things Hungary did, and had done to it, in the century since.
Answer: | noise | This dismemberment helps explain many of the worst things Hungary did, and had done to it, in the century since. | [
"noise",
"causal"
] | 0 |
causal20sc272 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Hitler helped the country recover some of its territories in World War II, but Russia repressed them and then some.
Answer: | noise | Hitler helped the country recover some of its territories in World War II, but Russia repressed them and then some. | [
"noise",
"causal"
] | 0 |
causal20sc273 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The historic heart of Hungary is Transylvania, now on the other side of the Romanian border. Other ethnically Hungarian remnants of the nation are to be found in Serbia, Slovakia, and Ukraine.
Answer: | noise | The historic heart of Hungary is Transylvania, now on the other side of the Romanian border. Other ethnically Hungarian remnants of the nation are to be found in Serbia, Slovakia, and Ukraine. | [
"noise",
"causal"
] | 0 |
causal20sc274 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Orbán is fond of a bitter, Trianon-era joke to the effect that Hungary is the only country that borders on itself.
Answer: | noise | Orbán is fond of a bitter, Trianon-era joke to the effect that Hungary is the only country that borders on itself. | [
"noise",
"causal"
] | 0 |
causal20sc275 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: It is as a nation of 15 million, and not as a state of 10 million, that most Hungarians understand themselves, and Orbán has done nothing to bring them to a more liberal understanding. Hungary's most acute present-day problems are partly the result of its four decades under Communism, including the Soviet Union's bloody suppression of its 1956 uprising.
Answer: | noise | It is as a nation of 15 million, and not as a state of 10 million, that most Hungarians understand themselves, and Orbán has done nothing to bring them to a more liberal understanding. Hungary's most acute present-day problems are partly the result of its four decades under Communism, including the Soviet Union's bloody suppression of its 1956 uprising. | [
"noise",
"causal"
] | 0 |
causal20sc276 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: But, like contemporary Russia, the country suffers just as much from the excess of faith it placed in Western expertise during its botched transition out of Communism. One of Orbán's mentors recalls: We were all liberals then, using the term liberal to mean believers in markets.
Answer: | noise | But, like contemporary Russia, the country suffers just as much from the excess of faith it placed in Western expertise during its botched transition out of Communism. One of Orbán's mentors recalls: We were all liberals then, using the term liberal to mean believers in markets. | [
"noise",
"causal"
] | 0 |
causal20sc277 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: But about markets Hungarians had more enthusiasm than expertise.
Answer: | noise | But about markets Hungarians had more enthusiasm than expertise. | [
"noise",
"causal"
] | 0 |
causal20sc278 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: They sold off their best state-owned businesses to foreigners, and saw others taken over by savvy ex-members of the Communist nomenklatura, who knew where value lay hidden.
Answer: | noise | They sold off their best state-owned businesses to foreigners, and saw others taken over by savvy ex-members of the Communist nomenklatura, who knew where value lay hidden. | [
"noise",
"causal"
] | 0 |
causal20sc279 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: It was a trap, says one of Orbán's younger advisers.
Answer: | noise | It was a trap, says one of Orbán's younger advisers. | [
"noise",
"causal"
] | 0 |
causal20sc280 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: To open markets with no capital. Now we are trying to get out of that trap. For a Soviet satellite, Hungary had been advanced.
Answer: | noise | To open markets with no capital. Now we are trying to get out of that trap. For a Soviet satellite, Hungary had been advanced. | [
"noise",
"causal"
] | 0 |
causal20sc281 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The 1956 uprising had scared the Soviets.
Answer: | noise | The 1956 uprising had scared the Soviets. | [
"noise",
"causal"
] | 0 |
causal20sc282 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: They allowed János Kádár, the strongman who bottled up Hungarian dissent until the Reagan Administration, to borrow hard currency from the West.
Answer: | noise | They allowed János Kádár, the strongman who bottled up Hungarian dissent until the Reagan Administration, to borrow hard currency from the West. | [
"noise",
"causal"
] | 0 |
causal20sc283 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Budapest had its first Hilton in 1977.
Answer: | noise | Budapest had its first Hilton in 1977. | [
"noise",
"causal"
] | 0 |
causal20sc284 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: It soon had lots of debt, too. By the time the Berlin Wall fell the country's debt-to-GDP ratio hovered around 75%, a figure then considered beyond reckless but today about average for Western economies.
Answer: | noise | It soon had lots of debt, too. By the time the Berlin Wall fell the country's debt-to-GDP ratio hovered around 75%, a figure then considered beyond reckless but today about average for Western economies. | [
"noise",
"causal"
] | 0 |
causal20sc285 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Things got worse when the Wall came down. GDP fell 20% between 1988 and 1993. There were suddenly hundreds of thousands of unemployed in a country that, under Communism, had had full employment.
Answer: | causal | Things got worse when the Wall came down. GDP fell 20% between 1988 and 1993. There were suddenly hundreds of thousands of unemployed in a country that, under Communism, had had full employment. | [
"noise",
"causal"
] | 1 |
causal20sc286 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Hungary's population of gypsies, or Roma, had never been a perfect fit in society but now many came unstuck from their jobs and homes.
Answer: | noise | Hungary's population of gypsies, or Roma, had never been a perfect fit in society but now many came unstuck from their jobs and homes. | [
"noise",
"causal"
] | 0 |
causal20sc287 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: A nostalgia for Kádár arose that has not fully dissipated. Between 1994 and 1998 the supposedly free-market heirs to the anti-Communist dissidents ruled in coalition with former Communists.
Answer: | noise | A nostalgia for Kádár arose that has not fully dissipated. Between 1994 and 1998 the supposedly free-market heirs to the anti-Communist dissidents ruled in coalition with former Communists. | [
"noise",
"causal"
] | 0 |
causal20sc288 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Orbán took office in their wake, ran a responsible, lean, relatively patronage-free government for four years…and was bounced from office in 2002. That taught him a lesson.
Answer: | noise | Orbán took office in their wake, ran a responsible, lean, relatively patronage-free government for four years…and was bounced from office in 2002. That taught him a lesson. | [
"noise",
"causal"
] | 0 |
causal20sc289 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: The years 2002-10 saw the full restoration to power of those who in the 1980s had been trained as the next generation of Communist elites, dominated by the Socialist multimillionaire Ferenc Gyurcsány. Penury and soaring unemployment marked the time. In 2006, Gyurcsány was captured on tape at a party congress explaining that we lied, morning, noon and night to stay in power.
Answer: | noise | The years 2002-10 saw the full restoration to power of those who in the 1980s had been trained as the next generation of Communist elites, dominated by the Socialist multimillionaire Ferenc Gyurcsány. Penury and soaring unemployment marked the time. In 2006, Gyurcsány was captured on tape at a party congress explaining that we lied, morning, noon and night to stay in power. | [
"noise",
"causal"
] | 0 |
causal20sc290 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Protests arose. Police repressed them violently.
Answer: | noise | Protests arose. Police repressed them violently. | [
"noise",
"causal"
] | 0 |
causal20sc291 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Orbán's detractors rarely mention any of this when they complain about the lack of an alternative to him. For most Hungarians, 2006 is the alternative. Orbán returned to power in 2010 with a large enough majority in the National Assembly (two thirds) to rewrite the constitution from scratch.
Answer: | noise | Orbán's detractors rarely mention any of this when they complain about the lack of an alternative to him. For most Hungarians, 2006 is the alternative. Orbán returned to power in 2010 with a large enough majority in the National Assembly (two thirds) to rewrite the constitution from scratch. | [
"noise",
"causal"
] | 0 |
causal20sc292 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: He and his party Fidesz did so, in what he would provocatively call an illiberal way: setting Christianity at the middle of Hungarian life, declaring marriage to be between a man and a woman, banning genetically modified organisms. On top of that, Orbán was re-elected with two-thirds majorities in both 2014 and 2018, enabling him to fine-tune these arrangements, and add more, as he saw fit. Economic Turnaround Orbán was happy to pick fights with liberal rule-makers in the realm of politics.
Answer: | noise | He and his party Fidesz did so, in what he would provocatively call an illiberal way: setting Christianity at the middle of Hungarian life, declaring marriage to be between a man and a woman, banning genetically modified organisms. On top of that, Orbán was re-elected with two-thirds majorities in both 2014 and 2018, enabling him to fine-tune these arrangements, and add more, as he saw fit. Economic Turnaround Orbán was happy to pick fights with liberal rule-makers in the realm of politics. | [
"noise",
"causal"
] | 0 |
causal20sc293 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: But he saw that, in an era of fast-moving international finance and pitiless debt markets, tiny, poor Hungary could challenge the global economy's liberal rule-makers only with extreme caution. You must stay economically successful, he warned in that 2015 Kötcse speech, because in the modern spirit of the age, even if you are right, or closest to a morally perfect position, if you are not economically successful you will be trampled underfoot.
Answer: | noise | But he saw that, in an era of fast-moving international finance and pitiless debt markets, tiny, poor Hungary could challenge the global economy's liberal rule-makers only with extreme caution. You must stay economically successful, he warned in that 2015 Kötcse speech, because in the modern spirit of the age, even if you are right, or closest to a morally perfect position, if you are not economically successful you will be trampled underfoot. | [
"noise",
"causal"
] | 0 |
causal20sc294 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: It was two years after the collapse of Lehman Brothers when Orbán got power back, with the crisis over the Euro and Greece's state finances at its height. His lightning-fast restoration of Hungary's financial credibility and economic performance is, even today, a foundation of his credibility and popularity.
Answer: | noise | It was two years after the collapse of Lehman Brothers when Orbán got power back, with the crisis over the Euro and Greece's state finances at its height. His lightning-fast restoration of Hungary's financial credibility and economic performance is, even today, a foundation of his credibility and popularity. | [
"noise",
"causal"
] | 0 |
causal20sc295 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: For Hungary was in a very similar position to Greece: heavily indebted, with 12% unemployment and an economy that had shrunk by 6.6% in the previous year.
Answer: | noise | For Hungary was in a very similar position to Greece: heavily indebted, with 12% unemployment and an economy that had shrunk by 6.6% in the previous year. | [
"noise",
"causal"
] | 0 |
causal20sc296 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Having acceded to the European Union under a disciplinary excessive deficit procedure in 2004, it risked becoming a permanent ward of continental regulators and the International Monetary Fund. When these authorities pressured Orbán to accept an austerity program like the one they were then devising for Greece - raising taxes and cutting services in order to pay off international banks - he refused.
Answer: | noise | Having acceded to the European Union under a disciplinary excessive deficit procedure in 2004, it risked becoming a permanent ward of continental regulators and the International Monetary Fund. When these authorities pressured Orbán to accept an austerity program like the one they were then devising for Greece - raising taxes and cutting services in order to pay off international banks - he refused. | [
"noise",
"causal"
] | 0 |
causal20sc297 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: Instead, working with his bold economics minister György Matolcsy, he pursued policies decried at the time as radical and irresponsible. He raised the minimum wage. He cut personal income tax rates sharply, from 30% to a flat rate of 16% (they would fall further, and corporate rates would bottom out at 9%, the lowest in Europe).
Answer: | causal | Instead, working with his bold economics minister György Matolcsy, he pursued policies decried at the time as radical and irresponsible. He raised the minimum wage. He cut personal income tax rates sharply, from 30% to a flat rate of 16% (they would fall further, and corporate rates would bottom out at 9%, the lowest in Europe). | [
"noise",
"causal"
] | 1 |
causal20sc298 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: He made up for those cuts by introducing special sectorial taxes on companies that had emerged from the financial crisis intact, and had even profited from it - mostly foreign banks, energy companies, and retailers. He nationalized pension funds - although this was more a bookkeeping arrangement than the radical program it was often presented as.
Answer: | noise | He made up for those cuts by introducing special sectorial taxes on companies that had emerged from the financial crisis intact, and had even profited from it - mostly foreign banks, energy companies, and retailers. He nationalized pension funds - although this was more a bookkeeping arrangement than the radical program it was often presented as. | [
"noise",
"causal"
] | 0 |
causal20sc299 | In this task, you are provided with sentences extracted from financial news and SEC data. Your goal is to classify each sentence into either 'causal' or 'noise' based on whether or not it indicates a causal relationship between financial events. Please return only the category 'causal' or 'noise'.
Text: And he averted a foreclosure catastrophe by convincing banks to accept payment in Hungarian forints for loans that Hungarian homeowners had taken out in Euros and Swiss Francs. He linked welfare to work.
Answer: | noise | And he averted a foreclosure catastrophe by convincing banks to accept payment in Hungarian forints for loans that Hungarian homeowners had taken out in Euros and Swiss Francs. He linked welfare to work. | [
"noise",
"causal"
] | 0 |