DataHammer/scimrc huggingface dataset:
Question: Which unlabeled data do they pretrain with?
Evidence: We consider pre-training on the audio data (without labels) of WSJ, part of clean Librispeech (about 80h) and full Librispeech as well as a combination of all datasets (§ SECREF7 ). For the pre-training experiments we feed the output of the context network to the acoustic model, instead of log-mel filterbank features.
Our experimental results on the WSJ benchmark demonstrate that pre-trained representations estimated on about 1,000 hours of unlabeled speech can substantially improve a character-based ASR system and outperform the best character-based result in the literature, Deep Speech 2. On the TIMIT task, pre-training enables us to match the best reported result in the literature. In a simulated low-resource setup with only eight hours of transcriped audio data, reduces WER by up to 32% compared to a baseline model that relies on labeled data only (§ SECREF3 & § SECREF4 ).
We consider pre-training on the audio data (without labels) of WSJ, part of clean Librispeech (about 80h) and full Librispeech as well as a combination of all datasets (§ SECREF7 ). 
Our experimental results on the WSJ benchmark demonstrate that pre-trained representations estimated on about 1,000 hours of unlabeled speech can substantially improve a character-based ASR system and outperform the best character-based result in the literature, Deep Speech 2. 
Answer: 1000 hours of WSJ audio data
Question: Sell me this pencil
Answer: I’m not sure that this pencil is right for you.  First, I would need to know more about why you need a pencil and what you will use it for.  Once we discuss your requirements, we can determine if this specific pencil is a good fit for your needs.
Question: Based on the given text, what is the population growth rate of Afghanistan since 1979?
Evidence: The population of Afghanistan was estimated at 32.9 million as of 2019 by the Afghanistan Statistics and Information Authority, whereas the UN estimates over 38.0 million. In 1979 the total population was reported to be about 15.5 million. About 23.9% of them are urbanite, 71.4% live in rural areas, and the remaining 4.7% are nomadic. An additional 3 million or so Afghans are temporarily housed in neighboring Pakistan and Iran, most of whom were born and raised in those two countries.
Answer: There are varying accounts of the population of Afghanistan. The Afghanistan Statistics and Information Authority estimated the population at 32.9 million in 2019 whereas the UN estimates it at 38.90 million. In 1979 the total population was reported to be about 15.5 million. Using the following formula:

Percentage Increase = ((Final Value - Starting Value)/(Starting Value)) * 100

Using the Afghan Statistics and Information Authority Estimate:

Percentage Increase = ((32.9 - 15.5)/(15.5)) * 100 = 112.25%

Using the UN Estimate:

Percentage Increase = ((38.90 - 15.5)/(15.5)) * 100 = 150.96%

Therefore, the percentage growth rate of the population of Afghanistan is either 112.25% (Afghan Statistics and Information Authority) or 150.96% (UN) based on the two estimates provided.
Question: What is the most prominent street in Copenhagen Denmark?
Evidence: Bredgade (lit. "Broad Street") is one of the most prominent streets in Copenhagen, Denmark. Running in a straight line from Kongens Nytorv for just under one kilometre to the intersection of Esplanaden and Grønningen, it is one of the major streets in Frederiksstaden, a Rococo district laid out in the middle of the 18th century to commemorate the tercentenary of the House of Oldenburg's accession to the Danish throne. It is lined with a number of fine mansions as well as other historic buildings. Many law firms, trade unions, fashion stores and art galleries are based in the street.
Answer: Bredgade is the most prominent street in Denmark. It was created in the middle of the 18th century to commemorate teh House of Oldenburg's ascension to the Danish throne.
Question: What were the reasons for Enzo Ferrari to leave Alfa Romeo and start his own auto company?
Answer: In 1937 Enzo Ferrari quit Alfa-Romeo under agreement that he could not race or design anything under his name for four years. During World War II, Ferrari's company was forced to undertake war production for Mussolini's fascist government, thus supplying auto parts for the Italian military.
Question: What is used in the coding process?
Evidence: Automated coding of political event data, or the record of who-did-what-to-whom within the context of political actions, has existed for roughly two decades. The approach has remained largely the same during this time, with the underlying coding procedures not updating to reflect changes in natural language processing (NLP) technology. These NLP technologies have now advanced to such a level, and with accompanying open-source software implementations, that their inclusion in the event-data coding process comes as an obvious advancement. When combined with changes in how news content is obtained, the ability to store and process large amounts of text, and enhancements based on two decades worth of event-data experience, it becomes clear that political event data is ready for a next generation dataset.
In this chapter, I provide the technical details for creating such a next-generation dataset. The technical details lead to a pipeline for the production of the Phoenix event dataset. The Phoenix dataset is a daily updated, near-real-time political event dataset. The coding process makes use of open-source NLP software, an abundance of online news content, and other technical advances made possible by open-source software. This enables a dataset that is transparent and replicable, while providing a more accurate coding process than previously possible. Additionally, the dataset's near-real-time nature also enables many applications that were previously impossible with batch-updated datasets, such as monitoring of ongoing events. Thus, this dataset provides a significant improvement over previous event data generation efforts.
In the following sections I briefly outline the history of computer-generated political event data to this point in history. I then outline what the “next generation” of event data should look like. Following this, I discuss the many facets of creating a real-time political event dataset, mainly from a technological and infrastructure standpoint. Finally, the paper concludes with a brief empirical view of the Phoenix event dataset, which is the output of the previously-discussed technological pipeline.
The coding process makes use of open-source NLP software, an abundance of online news content, and other technical advances made possible by open-source software.
Answer: Open-source NLP software, an abundance of online news content, and other technical advances made possible by open-source software.
Question: How to learn or do something complex?
Answer: Nothing in the world is complex if you break down into the bits and pieces that made it. What you see as a complex thing is a person or multiple persons spending a lot of time adding more pieces on top of a very simple design. So the easiest way to do or learn something complex is to learn the basic first and try to build something your own. Once you are on that path you will see how a simple thought or design evolves in complexity as you stabilize your design to cater to a wider set of uses.
Question: Approx. how many nurses were enrolled in World War 2?
Answer: More than 100,000 nurses were enrolled to the Red Cross during WW2
Question: Identify which instrument is string or percussion: Triangle, Pinaka vina
Answer: Pinaka vina is string, Triangle is percussion.
Question: What provoked the civil unrest incidents which started in 19th January 2023 in France based on the below passage?
Evidence: A series of civil unrest incidents began in France on 19 January 2023, organised by opponents of the pension reform bill proposed by the Borne government, which would increase the retirement age from 62 to 64 years old. The strikes have led to widespread disruption, including garbage piling up in the streets and public transport cancellations. In March, the government used Article 49.3 of the constitution to force the bill through the French Parliament, sparking more protests and two failed no confidence votes, contributing to an increase in violence in protests alongside the union-organised strike action.
Several organizations, including human rights groups such as Reporters Without Borders and France's Human Rights League condemned France's crackdown on protests and also denounced the assault on journalists. In addition, the Council of Europe also criticised the "excessive use of force by agents of the state".
Answer: The civil unrest in France on 19 January 2023 was provoked by the new proposal from the Borne government to increase retirement age.The current retirement age is 62, which is proposed to be increased to 64. Opponents of the bill organised protests against the government who used Article 49.3 of the constitution to force the bill through the parliament .
Question: Who is the greatest physicist of all time?
Answer: There have been many great physicists over the years, and while it's not possible to say with certainty who was the 'greatest', Isaac Newton and Albert Einstein are very strong contenders for that title.

Isaac Newton (1642-1746) was an English physicist and mathematician  most famous for inventing calculus, classical mechanics. His three laws of classical mechanics successfully predicted the behavior of solid bodies across all observable scales - from the motion of planets to falling apples. For over 250 years his laws were applied with greater and greater precision, always giving the correct answers.

However, in the late 1800s physicists struggled to reconcile measurements of the speed of light with Newton's laws. This one of the observations that led to Einstein's Special Theory of Relativity.

Albert Einstein (1879-1955) was a German-born physicist who revolutionized our understanding of space, time and matter with his theories of relativity and quantum mechanics. His theories of special and general relativity changed our understanding of space and time and successfully explained the motion of light and the behavior of gravity.  His theories of quantum mechanics likewise revolutionized our understand of the sub-atomic world.

In addition to Newton and Einstein there are many other physicists who made groundbreaking discoveries,  including Galileo Galilei, James Clerk Maxwell,  Marie Curie, Neils Bohr, Richard Feynman, and Stephen Hawking.
Question: Without quoting directly from the text give me a summary of the history of the Key Lime Pie.
Evidence: Key lime pie is probably derived from the "Magic Lemon Cream Pie" published in a promotional brochure by Borden, a producer of condensed milk, in 1931. The recipe is attributed to Borden's fictional spokesperson, Jane Ellison, and includes condensed milk, lemon juice and rind, and egg yolks. It is covered with meringue, baked, and served cold. According to the pastry chef Stella Parks, users of the recipe altered it with local ingredients; she describes it as "a stunning reminder of how deeply America's traditions are shaped by advertising".

A "Tropical Lime Chiffon Pie", using condensed milk and egg yolks, is documented in a 1933 Miami newspaper article. An "icebox lime pie", was mentioned as a specialty of the Florida Keys in 1935.[full citation needed] and a recipe under the name "Key Lime Pie" was published in 1940.[full citation needed]

No earlier solid sources are known, despite appeals to the public. A 1927 Key West Women's Club cookbook does not mention the recipe. A 1926 restaurant menu includes "lime pie", but it is unclear what it was. Various accounts claim that it was known earlier, but none were recorded before 1933. A widely-reported story claims that William Curry's cook Aunt Sally invented it in the late 19th century. But there is no evidence for this, and the oldest version of this story dates to only 1895, in promotional materials for a Bed and Breakfast in Curry's former house.

It was in the 1950s that Key lime pie was promoted as Florida's "most famous treat" and in 1987 as "the greatest of all regional American desserts."
Answer: Key lime pie is an American dessert pie. It is made of lime juice, egg yolks, and sweetened condensed milk. It is best served with meringue topping and is typically cooked in a graham cracker crust.

The dish is named after the small Key limes which which have yellow juice complementing the filling which is typically yellow because of the egg yolks used.

The filling is made by simply mixing the ingredients without cooking the proteins of the egg yolks and condensed milk and the acidic lime juice curdle, thickening the mixture without baking.
Question: What is a Central Bank?
Answer: A central bank, reserve bank, or monetary authority is an institution that manages the currency and monetary policy of a country or monetary union, and oversees their commercial banking system. In contrast to a commercial bank, a central bank possesses a monopoly on increasing the monetary base. Most central banks also have supervisory and regulatory powers to ensure the stability of member institutions, to prevent bank runs, and to discourage reckless or fraudulent behavior by member banks.
Question: Give me a simple summary of idempotency
Evidence: Idempotence (UK: /ˌɪdɛmˈpoʊtəns/, US: /ˈaɪdəm-/) is the property of certain operations in mathematics and computer science whereby they can be applied multiple times without changing the result beyond the initial application. The concept of idempotence arises in a number of places in abstract algebra (in particular, in the theory of projectors and closure operators) and functional programming (in which it is connected to the property of referential transparency).

The term was introduced by American mathematician Benjamin Peirce in 1870 in the context of elements of algebras that remain invariant when raised to a positive integer power, and literally means "(the quality of having) the same power", from idem + potence (same + power).
Answer: Idempotency is a mathematical property where if you apply an operation multiple times, the result remains the same -- just as if you had only applied the operation once. Idempotency can grant you at-most-once semantics.
Question: Why are weddings so expensive?
Answer: In 2023, the wedding industry continues to raise its prices. There are many things to account for like the cost of food and beverage, as well as service and decorations. Flowers need to be cared for and require skill creating arrangements. Other costs to consider when planning a wedding are hair and makeup costs, ceremony music, transportation for your guests, reception music, a stage, a dance floor, lighting such as uplighting, table decor, and many other items. It all adds up. Plus, don't forget budgeting for tips.
Question: Where should I fly fish for trout in Washington state?
Answer: Some of the popular bodies of water to fish for trout in Washington state are the Yakima River, Naches River, the Middle Fork of the Snoqualmie, and the beaches of the puget sound. You can also find excellent trout fishing in Washington’s high lakes, although not all lakes are able to support a healthy population of trout.
Question: What is the limitation of the unsupervised approach in the case?
Evidence: Suppose a user wants to write a sentence “I will be 10 minutes late.” Ideally, she would type just a few keywords such as “10 minutes late” and an autocomplete system would be able to infer the intended sentence (Figure FIGREF1). Existing left-to-right autocomplete systems BIBREF0, BIBREF1 can often be inefficient, as the prefix of a sentence (e.g. “I will be”) fails to capture the core meaning of the sentence. Besides the practical goal of building a better autocomplete system, we are interested in exploring the tradeoffs inherent to such communication schemes between the efficiency of typing keywords, accuracy of reconstruction, and interpretability of keywords.
One approach to learn such schemes is to collect a supervised dataset of keywords-sentence pairs as a training set, but (i) it would be expensive to collect such data from users, and (ii) a static dataset would not capture a real user's natural predilection to adapt to the system BIBREF2. Another approach is to avoid supervision and jointly learn a user-system communication scheme to directly optimize the combination of efficiency and accuracy. However, learning in this way can lead to communication schemes that are uninterpretable to humans BIBREF3, BIBREF4 (see Appendix for additional related work).
In this work, we propose a simple, unsupervised approach to an autocomplete system that is efficient, accurate, and interpretable. For interpretability, we restrict keywords to be subsequences of their source sentences based on the intuition that humans can infer most of the original meaning from a few keywords. We then apply multi-objective optimization approaches to directly control and achieve desirable tradeoffs between efficiency and accuracy.
We observe that naively optimizing a linear combination of efficiency and accuracy terms is unstable and leads to suboptimal schemes. Thus, we propose a new objective which optimizes for communication efficiency under an accuracy constraint. We show this new objective is more stable and efficient than the linear objective at all accuracy levels.
As a proof-of-concept, we build an autocomplete system within this framework which allows a user to write sentences by specifying keywords. We empirically show that our framework produces communication schemes that are 52.16% more accurate than rule-based baselines when specifying 77.37% of sentences, and 11.73% more accurate than a naive, weighted optimization approach when specifying 53.38% of sentences. Finally, we demonstrate that humans can easily adapt to the keyword-based autocomplete system and save nearly 50% of time compared to typing a full sentence in our user study.
Another approach is to avoid supervision andjointly learn a user-system communication scheme to directly optimize the combination of efficiency and accuracy. However, learning in this way can lead to communication schemes that are uninterpretable to humans [21, 27] (see Appendix A for additional related work).
Answer: It can lead to communication schemes that are uninterpretable to humans.
Question: How does their model learn using mostly raw data?
Evidence: In this paper, we propose a simple and effective method for learning affective events that only requires a very small seed lexicon and a large raw corpus. As illustrated in Figure FIGREF1, our key idea is that we can exploit discourse relations BIBREF4 to efficiently propagate polarity from seed predicates that directly report one's emotions (e.g., “to be glad” is positive). Suppose that events $x_1$ are $x_2$ are in the discourse relation of Cause (i.e., $x_1$ causes $x_2$). If the seed lexicon suggests $x_2$ is positive, $x_1$ is also likely to be positive because it triggers the positive emotion. The fact that $x_2$ is known to be negative indicates the negative polarity of $x_1$. Similarly, if $x_1$ and $x_2$ are in the discourse relation of Concession (i.e., $x_2$ in spite of $x_1$), the reverse of $x_2$'s polarity can be propagated to $x_1$. Even if $x_2$'s polarity is not known in advance, we can exploit the tendency of $x_1$ and $x_2$ to be of the same polarity (for Cause) or of the reverse polarity (for Concession) although the heuristic is not exempt from counterexamples. We transform this idea into objective functions and train neural network models that predict the polarity of a given event.
In this paper, we propose a simple and effective method for learning affective events that only requires a very small seed lexicon and a large raw corpus. As illustrated in Figure FIGREF1, our key idea is that we can exploit discourse relations BIBREF4 to efficiently propagate polarity from seed predicates that directly report one's emotions (e.g., “to be glad” is positive).
Answer: by exploiting discourse relations to propagate polarity from seed predicates to final sentiment polarity
Question: Tell me whether these are nouns or verbs: Run, Dance, Slide, Jump, Think, Book, Noah Webster, Cat, Omaha, Softness, Justice.
Answer: Run is a verb.
Dance is a verb.
Slide is a verb.
Jump is a verb.
Think is a verb.
Book is a noun.
Noah Webster is a noun.
Cat is a noun.
Omaha is a noun.
Softness is a noun.
Justice is a noun.
Question: What are some of the challenges when walking with crutches?
Answer: You will probably find it intuitive to use crutches to move around flat areas when you have a leg injury. You may not immediately know how to safely move up and down stairs with crutches, but there are many videos on the Internet that show clear examples of how to do so, with or without a handrail as support. One of the biggest challenges when using crutches is that they make it difficult to carry items from one place to another, because your hands are always holding the crutches. To overcome this challenge, it can be useful to have a backpack or a bag to help you carry things around while holding onto the crutches. Walking for long periods of time with crutches can also make your hands feel sore because they are not used to bearing your bodyweight for very long. Finally, it is important to make sure you always set down your crutches in stable positions against walls or furniture, as they can easily be knocked over by accidental touch or household pets.
Question: what are some types of vandalism?
Evidence: Any change or edit that manipulates content in a way that deliberately compromises Wikipedia's integrity is considered vandalism. The most common and obvious types of vandalism include additions of obscenities and crude humor; it can also include advertising and other types of spam. Sometimes editors commit vandalism by removing content or entirely blanking a given page. Less common types of vandalism, such as the deliberate addition of plausible but false information, can be more difficult to detect. Vandals can introduce irrelevant formatting, modify page semantics such as the page's title or categorization, manipulate the article's underlying code, or use images disruptively.
Answer: Some types of vandalism are obscenities and crude humor, advertising, deliberate addition of plausible but false information, and irrelevant formatting.
Question: Why do toddlers throw tantrums?
Answer: There are many triggers that may cause toddlers to throw a tantrum, such as hunger or exhaustion. But the reason that toddlers often lose control of their emotions and become seemingly inconsolable is that as toddlers develop emotionally, they start to experience new feelings or start to feel things more deeply. When they do not have the communication skills to express these experiences, to manage these experiences, or to ask for help with them, they resort to signaling that they are in distress.