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causal20sc700 | 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 rather by concentrating their money in the one stock they understood best. We have all heard of how important it is to diversify your investments.... However... today I'm going to reveal a dirty little secret of the investment world.
Answer: | noise | But rather by concentrating their money in the one stock they understood best. We have all heard of how important it is to diversify your investments.... However... today I'm going to reveal a dirty little secret of the investment world. | [
"noise",
"causal"
] | 0 |
causal20sc701 | 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 truth is... Sometimes diversification is not a good idea.
Answer: | noise | The truth is... Sometimes diversification is not a good idea. | [
"noise",
"causal"
] | 0 |
causal20sc702 | 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: Yes, I said it.
Answer: | noise | Yes, I said it. | [
"noise",
"causal"
] | 0 |
causal20sc703 | 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 I'm sure a few CPAs reading this just fainted.
Answer: | noise | And I'm sure a few CPAs reading this just fainted. | [
"noise",
"causal"
] | 0 |
causal20sc704 | 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 it's true nonetheless. When you find a single stock that's truly special, you can in fact retire on that one stock.
Answer: | noise | But it's true nonetheless. When you find a single stock that's truly special, you can in fact retire on that one stock. | [
"noise",
"causal"
] | 0 |
causal20sc705 | 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: Jeff Bezos got rich not by holding hundreds of stocks in a diversified account, but by concentrating his capital in the one stock he knew would succeed - Amazon.
Answer: | noise | Jeff Bezos got rich not by holding hundreds of stocks in a diversified account, but by concentrating his capital in the one stock he knew would succeed - Amazon. | [
"noise",
"causal"
] | 0 |
causal20sc706 | 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: Bill Gates did the same with Microsoft. Sam Walton did it with Wal-Mart.
Answer: | noise | Bill Gates did the same with Microsoft. Sam Walton did it with Wal-Mart. | [
"noise",
"causal"
] | 0 |
causal20sc707 | 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: Steve Jobs did it with Apple.
Answer: | noise | Steve Jobs did it with Apple. | [
"noise",
"causal"
] | 0 |
causal20sc708 | 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 Larry Page did the same with Google.
Answer: | noise | And Larry Page did the same with Google. | [
"noise",
"causal"
] | 0 |
causal20sc709 | 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: These people all got rich by concentrating their wealth in single stocks.
Answer: | noise | These people all got rich by concentrating their wealth in single stocks. | [
"noise",
"causal"
] | 0 |
causal20sc710 | 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: Of course, you might be thinking, Yes, but they are the founders of those companies.
Answer: | noise | Of course, you might be thinking, Yes, but they are the founders of those companies. | [
"noise",
"causal"
] | 0 |
causal20sc711 | 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's true. But their shareholders got rich right alongside them.
Answer: | noise | That's true. But their shareholders got rich right alongside them. | [
"noise",
"causal"
] | 0 |
causal20sc712 | 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: Many saw a small stake turn into many millions of dollars. That possibility is also available to you, if you find the right stock and take action.
Answer: | noise | Many saw a small stake turn into many millions of dollars. That possibility is also available to you, if you find the right stock and take action. | [
"noise",
"causal"
] | 0 |
causal20sc713 | 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: Thousands of Americans Have Retired by Identifying Just One Great Stock. Microsoft is a classic example.
Answer: | noise | Thousands of Americans Have Retired by Identifying Just One Great Stock. Microsoft is a classic example. | [
"noise",
"causal"
] | 0 |
causal20sc714 | 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: From its IPO to today, it's generated a healthy return of 98,000%.
Answer: | noise | From its IPO to today, it's generated a healthy return of 98,000%. | [
"noise",
"causal"
] | 0 |
causal20sc715 | 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: Every $2,000 turned into $1.96 million.
Answer: | noise | Every $2,000 turned into $1.96 million. | [
"noise",
"causal"
] | 0 |
causal20sc716 | 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: Bill Gates became a billionaire.
Answer: | noise | Bill Gates became a billionaire. | [
"noise",
"causal"
] | 0 |
causal20sc717 | 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 right alongside him, thousands of ordinary people also got rich.
Answer: | noise | But right alongside him, thousands of ordinary people also got rich. | [
"noise",
"causal"
] | 0 |
causal20sc718 | 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 New York Times estimates that at least 10,000 people became millionaires just from plunking a few dollars in the wildly profitable stock.
Answer: | causal | The New York Times estimates that at least 10,000 people became millionaires just from plunking a few dollars in the wildly profitable stock. | [
"noise",
"causal"
] | 1 |
causal20sc719 | 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 Microsoft Millionaires include people like...
Answer: | noise | The Microsoft Millionaires include people like... | [
"noise",
"causal"
] | 0 |
causal20sc720 | 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: Andrea Lewis, estimated to be worth $2 million, who started Hugo House, a center for writers in Seattle, with her profits. Jim Allchin, who retired and became a renowned blues guitarist Chris Peters, a bowling enthusiast, who cashed out and bought the Professional Bowlers Association for an estimated $5 million (and then promptly set it on track to turn profitable and double its revenue). For them, one stock did it all.
Answer: | causal | Andrea Lewis, estimated to be worth $2 million, who started Hugo House, a center for writers in Seattle, with her profits. Jim Allchin, who retired and became a renowned blues guitarist Chris Peters, a bowling enthusiast, who cashed out and bought the Professional Bowlers Association for an estimated $5 million (and then promptly set it on track to turn profitable and double its revenue). For them, one stock did it all. | [
"noise",
"causal"
] | 1 |
causal20sc721 | 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 gave them the freedom to escape the rat race and follow their dreams.
Answer: | noise | It gave them the freedom to escape the rat race and follow their dreams. | [
"noise",
"causal"
] | 0 |
causal20sc722 | 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's the same story with Amazon.
Answer: | noise | It's the same story with Amazon. | [
"noise",
"causal"
] | 0 |
causal20sc723 | 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's risen 106,500% since it came on the scene a split-adjusted $1.50 a share.
Answer: | causal | It's risen 106,500% since it came on the scene a split-adjusted $1.50 a share. | [
"noise",
"causal"
] | 1 |
causal20sc724 | 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: Every $1,000 turned into $1.06 million.
Answer: | noise | Every $1,000 turned into $1.06 million. | [
"noise",
"causal"
] | 0 |
causal20sc725 | 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: Amazon employees alone collect $1.5 BILLION in new wealth each year just because they own company stock.
Answer: | causal | Amazon employees alone collect $1.5 BILLION in new wealth each year just because they own company stock. | [
"noise",
"causal"
] | 1 |
causal20sc726 | 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'd say that's a pretty darn good Single-Stock Retirement Plan.
Answer: | noise | I'd say that's a pretty darn good Single-Stock Retirement Plan. | [
"noise",
"causal"
] | 0 |
causal20sc727 | 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: Facebook is another single stock you could have retired on.
Answer: | noise | Facebook is another single stock you could have retired on. | [
"noise",
"causal"
] | 0 |
causal20sc728 | 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 company contractor famously saw the value in the stock and collected a few shares. He turned every $1,000 into $3.3 million!
Answer: | noise | One company contractor famously saw the value in the stock and collected a few shares. He turned every $1,000 into $3.3 million! | [
"noise",
"causal"
] | 0 |
causal20sc729 | 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 then there's Apple.
Answer: | noise | And then there's Apple. | [
"noise",
"causal"
] | 0 |
causal20sc730 | 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 handed investors more than 124 times their money over the last 20 years.
Answer: | noise | The company has handed investors more than 124 times their money over the last 20 years. | [
"noise",
"causal"
] | 0 |
causal20sc731 | 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: Two grandparents, Joanie and Bill Miller from Buffalo, New York, decided to make Apple their Single-Stock Retirement Plan back in 1997. They put $16,000 into Apple stock. And since then, they've made $2 million.
Answer: | causal | Two grandparents, Joanie and Bill Miller from Buffalo, New York, decided to make Apple their Single-Stock Retirement Plan back in 1997. They put $16,000 into Apple stock. And since then, they've made $2 million. | [
"noise",
"causal"
] | 1 |
causal20sc732 | 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's a simple matter of fact: If you find The Perfect Stock you can and in fact WILL retire far wealthier that you ever could have imagined.
Answer: | noise | It's a simple matter of fact: If you find The Perfect Stock you can and in fact WILL retire far wealthier that you ever could have imagined. | [
"noise",
"causal"
] | 0 |
causal20sc733 | 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's what you ought to be looking for every day as an investor. Nothing can change your life more dramatically than a huge individual winner.
Answer: | noise | It's what you ought to be looking for every day as an investor. Nothing can change your life more dramatically than a huge individual winner. | [
"noise",
"causal"
] | 0 |
causal20sc734 | 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 you don't have to bet the farm on that single stock, either.
Answer: | noise | And you don't have to bet the farm on that single stock, either. | [
"noise",
"causal"
] | 0 |
causal20sc735 | 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: When you get in for around 5 cents per share, just a small sum can be enough to make your dreams a reality. The truth is... every once in a blue moon, I've found a stock so innovative, so brilliant in concept and so devastatingly profitable... that I've bet on this single stock.
Answer: | noise | When you get in for around 5 cents per share, just a small sum can be enough to make your dreams a reality. The truth is... every once in a blue moon, I've found a stock so innovative, so brilliant in concept and so devastatingly profitable... that I've bet on this single stock. | [
"noise",
"causal"
] | 0 |
causal20sc736 | 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: All it takes is identifying those perfect stocks that change everything.
Answer: | noise | All it takes is identifying those perfect stocks that change everything. | [
"noise",
"causal"
] | 0 |
causal20sc737 | 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 today, I've found what I'm convinced is the next great breakthrough Healthcare company.
Answer: | noise | And today, I've found what I'm convinced is the next great breakthrough Healthcare company. | [
"noise",
"causal"
] | 0 |
causal20sc738 | 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've never seen a firm better suited for the Single-Stock Retirement Plan. It's crazy cheap at around 5 cents a share.
Answer: | noise | I've never seen a firm better suited for the Single-Stock Retirement Plan. It's crazy cheap at around 5 cents a share. | [
"noise",
"causal"
] | 0 |
causal20sc739 | 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's virtually unknown to investors.
Answer: | noise | It's virtually unknown to investors. | [
"noise",
"causal"
] | 0 |
causal20sc740 | 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: Future revenues will likely go into the HUNDREDS of MILLIONS ..... more than most NASDAQ or NYSE stocks....yet it's share price is only around 5 cents right now!
Answer: | noise | Future revenues will likely go into the HUNDREDS of MILLIONS ..... more than most NASDAQ or NYSE stocks....yet it's share price is only around 5 cents right now! | [
"noise",
"causal"
] | 0 |
causal20sc741 | 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 in a moment, I'm going to give you it's name....here is just one example of why I'm so excited about this stock The average independent pharmacy fills approximately 5000 prescriptions per month or 60,000 per year.
Answer: | noise | And in a moment, I'm going to give you it's name....here is just one example of why I'm so excited about this stock The average independent pharmacy fills approximately 5000 prescriptions per month or 60,000 per year. | [
"noise",
"causal"
] | 0 |
causal20sc742 | 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 company is filling over 46000 scripts per month as of RIGHT NOW and will likely fill around 600,000 next year...and they are EXPANDING as thousand of new doctors and patients keep switching to them.
Answer: | noise | This company is filling over 46000 scripts per month as of RIGHT NOW and will likely fill around 600,000 next year...and they are EXPANDING as thousand of new doctors and patients keep switching to them. | [
"noise",
"causal"
] | 0 |
causal20sc743 | 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: You can see why I believe sales won't just be big....They are set to be ENORMOUS.
Answer: | noise | You can see why I believe sales won't just be big....They are set to be ENORMOUS. | [
"noise",
"causal"
] | 0 |
causal20sc744 | 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: Insiders hold a large percentage of shares and they have not sold a single share, they know what's coming!
Answer: | noise | Insiders hold a large percentage of shares and they have not sold a single share, they know what's coming! | [
"noise",
"causal"
] | 0 |
causal20sc745 | 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: Follow the insiders!
Answer: | noise | Follow the insiders! | [
"noise",
"causal"
] | 0 |
causal20sc746 | 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: Incredibly this under-the-radar Healthcare company is trading for around 5 cents per share. But not for long...
Answer: | noise | Incredibly this under-the-radar Healthcare company is trading for around 5 cents per share. But not for long... | [
"noise",
"causal"
] | 0 |
causal20sc747 | 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're looking at...hundreds and hundreds of millions in revenues!
Answer: | noise | We're looking at...hundreds and hundreds of millions in revenues! | [
"noise",
"causal"
] | 0 |
causal20sc748 | 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 don't think I've ever seen a 5 cent stock land this many landmark well structured investor friendly acquisition deals as it expands across the nation.
Answer: | noise | I don't think I've ever seen a 5 cent stock land this many landmark well structured investor friendly acquisition deals as it expands across the nation. | [
"noise",
"causal"
] | 0 |
causal20sc749 | 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 get an idea of how much revenue this Healthcare company is likely to make consider this.... The company is ALREADY filling almost 1500 prescriptions per day, thats over one prescription EVERY MINUTE of EVERY DAY 24 HOURS a day!
Answer: | noise | To get an idea of how much revenue this Healthcare company is likely to make consider this.... The company is ALREADY filling almost 1500 prescriptions per day, thats over one prescription EVERY MINUTE of EVERY DAY 24 HOURS a day! | [
"noise",
"causal"
] | 0 |
causal20sc750 | 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 this is just the beginning.
Answer: | noise | And this is just the beginning. | [
"noise",
"causal"
] | 0 |
causal20sc751 | 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 few years they will likely be filling close to a MILLION prescriptions per year as they expand into population dense areas up the Eastern Seaboard. Thats over 80,000 prescriptions per month...with no end in sight as expansion continues.
Answer: | causal | In the few years they will likely be filling close to a MILLION prescriptions per year as they expand into population dense areas up the Eastern Seaboard. Thats over 80,000 prescriptions per month...with no end in sight as expansion continues. | [
"noise",
"causal"
] | 1 |
causal20sc752 | 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 future I'm expecting total annual sales to surge to more than $100 million dollars...and then keep increasing from there. Who would've thought you could buy a company with that much sales potential for around 5 cents per share.
Answer: | noise | In the future I'm expecting total annual sales to surge to more than $100 million dollars...and then keep increasing from there. Who would've thought you could buy a company with that much sales potential for around 5 cents per share. | [
"noise",
"causal"
] | 0 |
causal20sc753 | 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's almost unheard of. The big question is...
Answer: | noise | It's almost unheard of. The big question is... | [
"noise",
"causal"
] | 0 |
causal20sc754 | 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: WHAT IS THIS NAME OF THIS STOCK?
Answer: | noise | WHAT IS THIS NAME OF THIS STOCK? | [
"noise",
"causal"
] | 0 |
causal20sc755 | 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 name of this little known Healthcare company that could change your life and and allow you to retire early and live the life you always dreamed of is Progressive Care (RXMD) Because when you combine a truly great business with virtual anonymity, that's when the gains can get truly spectacular. If you are still sitting on the fence about investing in Progressive Care (RXMD) consider these examples of what investing in Progressive Care (RXMD) could do for you: No-Name Stocks Work Best for Your Single-Stock Retirement Plan Ever heard of a stock called Balchem? It's based in the tiny town of Wawayanda, New York.
Answer: | noise | The name of this little known Healthcare company that could change your life and and allow you to retire early and live the life you always dreamed of is Progressive Care (RXMD) Because when you combine a truly great business with virtual anonymity, that's when the gains can get truly spectacular. If you are still sitting on the fence about investing in Progressive Care (RXMD) consider these examples of what investing in Progressive Care (RXMD) could do for you: No-Name Stocks Work Best for Your Single-Stock Retirement Plan Ever heard of a stock called Balchem? It's based in the tiny town of Wawayanda, New York. | [
"noise",
"causal"
] | 0 |
causal20sc756 | 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: Population: 7,266.
Answer: | noise | Population: 7,266. | [
"noise",
"causal"
] | 0 |
causal20sc757 | 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 business is pretty boring.
Answer: | noise | The business is pretty boring. | [
"noise",
"causal"
] | 0 |
causal20sc758 | 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's an animal nutrition and feed company that very few people have heard of. But like Progressive Care (RXMD) the 5 cent stock stock I'm talking about today, Balchem works behind the scenes supplying bigger-name companies. Yet it's handed investors 107,099% gains.
Answer: | noise | It's an animal nutrition and feed company that very few people have heard of. But like Progressive Care (RXMD) the 5 cent stock stock I'm talking about today, Balchem works behind the scenes supplying bigger-name companies. Yet it's handed investors 107,099% gains. | [
"noise",
"causal"
] | 0 |
causal20sc759 | 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: Imagine putting $2,000 in Balchem as your version of the Single-Stock Retirement Plan. All it would have taken was knowing the ticker symbol and placing the trade. And you'd be worth $2.1 million right now.
Answer: | noise | Imagine putting $2,000 in Balchem as your version of the Single-Stock Retirement Plan. All it would have taken was knowing the ticker symbol and placing the trade. And you'd be worth $2.1 million right now. | [
"noise",
"causal"
] | 0 |
causal20sc760 | 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: Then there's Danaher Corporation. It's a science and technology innovator based in Washington, D.C. Try bringing the company up at a cocktail party... people will think you're the least interesting person in the world.
Answer: | noise | Then there's Danaher Corporation. It's a science and technology innovator based in Washington, D.C. Try bringing the company up at a cocktail party... people will think you're the least interesting person in the world. | [
"noise",
"causal"
] | 0 |
causal20sc761 | 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: Yet it's a total blockbuster. Danaher's produced 144,100% gains.
Answer: | noise | Yet it's a total blockbuster. Danaher's produced 144,100% gains. | [
"noise",
"causal"
] | 0 |
causal20sc762 | 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: Back in the day, you could have gotten 20,000 shares for just $1,400. Now?
Answer: | noise | Back in the day, you could have gotten 20,000 shares for just $1,400. Now? | [
"noise",
"causal"
] | 0 |
causal20sc763 | 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: You'd be sitting on a dream retirement of $2.02 million.
Answer: | noise | You'd be sitting on a dream retirement of $2.02 million. | [
"noise",
"causal"
] | 0 |
causal20sc764 | 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: Altair Engineering is another one.
Answer: | noise | Altair Engineering is another one. | [
"noise",
"causal"
] | 0 |
causal20sc765 | 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 went from $0.30... to $3,501.
Answer: | noise | It went from $0.30... to $3,501. | [
"noise",
"causal"
] | 0 |
causal20sc766 | 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's a mind-boggling return of 1,166,900%!
Answer: | noise | That's a mind-boggling return of 1,166,900%! | [
"noise",
"causal"
] | 0 |
causal20sc767 | 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 single $100 bill in Altair would have built up a $1.1 million retirement account. Kansas City Southern is yet another stock that could have funded your whole retirement.
Answer: | noise | A single $100 bill in Altair would have built up a $1.1 million retirement account. Kansas City Southern is yet another stock that could have funded your whole retirement. | [
"noise",
"causal"
] | 0 |
causal20sc768 | 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: Every $20,000 turned into $1.38 million. Jack Henry & Associates was another blockbuster.
Answer: | noise | Every $20,000 turned into $1.38 million. Jack Henry & Associates was another blockbuster. | [
"noise",
"causal"
] | 0 |
causal20sc769 | 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: Let's say you bet $1,500 on it. Your retirement account today would be 174,271% higher.
Answer: | noise | Let's say you bet $1,500 on it. Your retirement account today would be 174,271% higher. | [
"noise",
"causal"
] | 0 |
causal20sc770 | 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: You'd have $2.61 million to play with. This is the power of finding an unknown stock that's delivering record sales and gargantuan profits. Of course, winners like Balchem and Altair aren't everyday occurrences.
Answer: | noise | You'd have $2.61 million to play with. This is the power of finding an unknown stock that's delivering record sales and gargantuan profits. Of course, winners like Balchem and Altair aren't everyday occurrences. | [
"noise",
"causal"
] | 0 |
causal20sc771 | 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 gains this big take time to develop.
Answer: | noise | And gains this big take time to develop. | [
"noise",
"causal"
] | 0 |
causal20sc772 | 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: Very few penny stocks ever turn into historic winners. It takes hundreds and sometimes thousands of hours of due diligence to uncover those rare, exceptional stocks where massive sales growth and near obscurity come together to create a perfect storm of profits.
Answer: | noise | Very few penny stocks ever turn into historic winners. It takes hundreds and sometimes thousands of hours of due diligence to uncover those rare, exceptional stocks where massive sales growth and near obscurity come together to create a perfect storm of profits. | [
"noise",
"causal"
] | 0 |
causal20sc773 | 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: Yet with Progressive Care (RXMD) you have a special opportunity in front of you today with this 5 cents stock, but you'll have to move quickly on this.
Answer: | noise | Yet with Progressive Care (RXMD) you have a special opportunity in front of you today with this 5 cents stock, but you'll have to move quickly on this. | [
"noise",
"causal"
] | 0 |
causal20sc774 | 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 remained almost completely anonymous until now. But I believe that's about to change in a big way.
Answer: | noise | The company has remained almost completely anonymous until now. But I believe that's about to change in a big way. | [
"noise",
"causal"
] | 0 |
causal20sc775 | 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 expect this stock will not stay ultra-cheap for long.
Answer: | noise | I expect this stock will not stay ultra-cheap for long. | [
"noise",
"causal"
] | 0 |
causal20sc776 | 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 big Wall Street sharks are starting to circle... quietly building up multimillion-dollar positions in preparation for the company to suddenly become a household name.
Answer: | noise | The big Wall Street sharks are starting to circle... quietly building up multimillion-dollar positions in preparation for the company to suddenly become a household name. | [
"noise",
"causal"
] | 0 |
causal20sc777 | 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 very rare to find a stock like Progressive Care (RXMD) trading at such a low level around 5 cents a share....it could be the best stock investment most of us may ever make.
Answer: | noise | It is very rare to find a stock like Progressive Care (RXMD) trading at such a low level around 5 cents a share....it could be the best stock investment most of us may ever make. | [
"noise",
"causal"
] | 0 |
causal20sc778 | 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 THE #1 stock to buy right now, easily one of the most undervalued stocks in America.
Answer: | noise | It is THE #1 stock to buy right now, easily one of the most undervalued stocks in America. | [
"noise",
"causal"
] | 0 |
causal20sc779 | 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: Progressive Care (RXMD) is under the radar, a high integrity growth and value stock being run with a code of ethics using world class best business practices and governance making it one of the best stock investments for 2019.
Answer: | noise | Progressive Care (RXMD) is under the radar, a high integrity growth and value stock being run with a code of ethics using world class best business practices and governance making it one of the best stock investments for 2019. | [
"noise",
"causal"
] | 0 |
causal20sc780 | 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: Progressive Care (RXMD) truly is an amazing value stock that come along once in a blue moon, value investing made Warren Buffett one of the best investors!
Answer: | noise | Progressive Care (RXMD) truly is an amazing value stock that come along once in a blue moon, value investing made Warren Buffett one of the best investors! | [
"noise",
"causal"
] | 0 |
causal20sc781 | 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: Value investing entails the fundamental analysis of a company's earnings power versus its current share price.
Answer: | noise | Value investing entails the fundamental analysis of a company's earnings power versus its current share price. | [
"noise",
"causal"
] | 0 |
causal20sc782 | 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: Value investing has made Warren Buffett and many of his colleagues famously rich.
Answer: | noise | Value investing has made Warren Buffett and many of his colleagues famously rich. | [
"noise",
"causal"
] | 0 |
causal20sc783 | 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: Not a bad model to emulate, now is the time to buy shares of Progressive Care (RXMD).
Answer: | noise | Not a bad model to emulate, now is the time to buy shares of Progressive Care (RXMD). | [
"noise",
"causal"
] | 0 |
causal20sc784 | 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: Renishaw plc (LON:RSW) declared a dividend on Thursday, August 1st, Upcoming.Co.Uk reports. Shareholders of record on Thursday, September 26th will be given a dividend of GBX 46 ($0.60) per share on Thursday, October 31st. This represents a yield of 1.26%.
Answer: | causal | Renishaw plc (LON:RSW) declared a dividend on Thursday, August 1st, Upcoming.Co.Uk reports. Shareholders of record on Thursday, September 26th will be given a dividend of GBX 46 ($0.60) per share on Thursday, October 31st. This represents a yield of 1.26%. | [
"noise",
"causal"
] | 1 |
causal20sc785 | 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 ex-dividend date is Thursday, September 26th. This is a boost from Renishaw's previous dividend of $14.00.
Answer: | noise | The ex-dividend date is Thursday, September 26th. This is a boost from Renishaw's previous dividend of $14.00. | [
"noise",
"causal"
] | 0 |
causal20sc786 | 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: Renishaw stock opened at GBX 3,662 ($47.85) on Tuesday. The company has a quick ratio of 2.71, a current ratio of 4.27 and a debt-to-equity ratio of 1.78.
Answer: | noise | Renishaw stock opened at GBX 3,662 ($47.85) on Tuesday. The company has a quick ratio of 2.71, a current ratio of 4.27 and a debt-to-equity ratio of 1.78. | [
"noise",
"causal"
] | 0 |
causal20sc787 | 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 firm has a 50-day moving average price of GBX 3,646.43 and a two-hundred day moving average price of GBX 3,956.63. The firm has a market capitalization of $2.68 billion and a price-to-earnings ratio of 28.90. Renishaw has a 52-week low of GBX 3,338 ($43.62) and a 52-week high of GBX 5,020 ($65.60).
Answer: | noise | The firm has a 50-day moving average price of GBX 3,646.43 and a two-hundred day moving average price of GBX 3,956.63. The firm has a market capitalization of $2.68 billion and a price-to-earnings ratio of 28.90. Renishaw has a 52-week low of GBX 3,338 ($43.62) and a 52-week high of GBX 5,020 ($65.60). | [
"noise",
"causal"
] | 0 |
causal20sc788 | 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: Renishaw (LON:RSW) last posted its earnings results on Thursday, August 1st. The company reported GBX 119.90 ($1.57) earnings per share (EPS) for the quarter, missing analysts' consensus estimates of GBX 129.20 ($1.69) by GBX (9.30) (($0.12)). A number of brokerages have recently weighed in on RSW.
Answer: | noise | Renishaw (LON:RSW) last posted its earnings results on Thursday, August 1st. The company reported GBX 119.90 ($1.57) earnings per share (EPS) for the quarter, missing analysts' consensus estimates of GBX 129.20 ($1.69) by GBX (9.30) (($0.12)). A number of brokerages have recently weighed in on RSW. | [
"noise",
"causal"
] | 0 |
causal20sc789 | 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: Morgan Stanley reaffirmed an equal weight rating on shares of Renishaw in a research note on Thursday, July 11th.
Answer: | noise | Morgan Stanley reaffirmed an equal weight rating on shares of Renishaw in a research note on Thursday, July 11th. | [
"noise",
"causal"
] | 0 |
causal20sc790 | 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: UBS Group reaffirmed a sell rating on shares of Renishaw in a research note on Thursday, September 12th. Goldman Sachs Group reaffirmed a neutral rating on shares of Renishaw in a research note on Wednesday, July 10th.
Answer: | noise | UBS Group reaffirmed a sell rating on shares of Renishaw in a research note on Thursday, September 12th. Goldman Sachs Group reaffirmed a neutral rating on shares of Renishaw in a research note on Wednesday, July 10th. | [
"noise",
"causal"
] | 0 |
causal20sc791 | 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: Investec lowered shares of Renishaw to a sell rating and reduced their price target for the stock from GBX 3,810 ($49.78) to GBX 3,745 ($48.94) in a research note on Tuesday, May 28th.
Answer: | noise | Investec lowered shares of Renishaw to a sell rating and reduced their price target for the stock from GBX 3,810 ($49.78) to GBX 3,745 ($48.94) in a research note on Tuesday, May 28th. | [
"noise",
"causal"
] | 0 |
causal20sc792 | 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: Finally, Deutsche Bank reaffirmed a sell rating on shares of Renishaw in a research note on Friday, July 12th. Five equities research analysts have rated the stock with a sell rating and three have issued a hold rating to the stock. The company currently has a consensus rating of Sell and a consensus price target of GBX 3,693.57 ($48.26).
Answer: | causal | Finally, Deutsche Bank reaffirmed a sell rating on shares of Renishaw in a research note on Friday, July 12th. Five equities research analysts have rated the stock with a sell rating and three have issued a hold rating to the stock. The company currently has a consensus rating of Sell and a consensus price target of GBX 3,693.57 ($48.26). | [
"noise",
"causal"
] | 1 |
causal20sc793 | 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: Renishaw Company Profile Renishaw plc, a metrology company, designs, manufactures, distributes, sells, and services metrology and healthcare products worldwide.
Answer: | noise | Renishaw Company Profile Renishaw plc, a metrology company, designs, manufactures, distributes, sells, and services metrology and healthcare products worldwide. | [
"noise",
"causal"
] | 0 |
causal20sc794 | 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 offers metrology products, including additive manufacturing systems, co-ordinate measuring machine products, machine tool probe systems, styli for probe systems, performance testing products, gauging systems, fixtures, and position encoders.
Answer: | noise | The company offers metrology products, including additive manufacturing systems, co-ordinate measuring machine products, machine tool probe systems, styli for probe systems, performance testing products, gauging systems, fixtures, and position encoders. | [
"noise",
"causal"
] | 0 |
causal20sc795 | 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: Social Security's been a fact of retirement life ever since it was established in 1935.
Answer: | noise | Social Security's been a fact of retirement life ever since it was established in 1935. | [
"noise",
"causal"
] | 0 |
causal20sc796 | 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 all think we know how it works, but how much do you really know?
Answer: | noise | We all think we know how it works, but how much do you really know? | [
"noise",
"causal"
] | 0 |
causal20sc797 | 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: Here are nine things that might surprise you.
Answer: | noise | Here are nine things that might surprise you. | [
"noise",
"causal"
] | 0 |
causal20sc798 | 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 Social Security trust fund is huge.
Answer: | noise | The Social Security trust fund is huge. | [
"noise",
"causal"
] | 0 |
causal20sc799 | 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 $2.9 trillion at the end of 2017, it exceeds the gross domestic product (GDP) of every economy in the world except the nine largest: China, the European Union, the United States, India, Japan, Germany, Russia, Indonesia, and Brazil.
Answer: | noise | At $2.9 trillion at the end of 2017, it exceeds the gross domestic product (GDP) of every economy in the world except the nine largest: China, the European Union, the United States, India, Japan, Germany, Russia, Indonesia, and Brazil. | [
"noise",
"causal"
] | 0 |