DataHammer/scimrc huggingface dataset:
Question: Do sluice networks outperform non-transfer learning approaches?
Evidence: FLOAT SELECTED: Table 3: Accuracy scores on in-domain and out-of-domain test sets for chunking (main task) with POS tagging as auxiliary task for different target domains for baselines and Sluice networks. Out-of-domain results for each target domain are averages across the 6 remaining source domains. Average error reduction over single-task performance is 12.8% for in-domain; 8.9% for out-of-domain. In-domain error reduction over hard parameter sharing is 14.8%.
FLOAT SELECTED: Table 3: Accuracy scores on in-domain and out-of-domain test sets for chunking (main task) with POS tagging as auxiliary task for different target domains for baselines and Sluice networks. Out-of-domain results for each target domain are averages across the 6 remaining source domains. Average error reduction over single-task performance is 12.8% for in-domain; 8.9% for out-of-domain. In-domain error reduction over hard parameter sharing is 14.8%.
Answer: Yes.
Question: Who is the Avatar? And what was he trying to accomplish?
Evidence: Avatar: The Last Airbender (abbreviated as ATLA), also known as Avatar: The Legend of Aang in some regions or simply Avatar, is an American animated fantasy action television series created by Michael Dante DiMartino and Bryan Konietzko and produced by Nickelodeon Animation Studio.

Avatar is set in an Asiatic-inspired world in which some people can telekinetically manipulate one of the four elements—water, earth, fire or air—through practices known as "bending", inspired by Chinese martial arts. The only individual who can bend all four elements, the "Avatar", is responsible for maintaining harmony among the world's four nations, and serves as the link between the physical world and the spirit world. The series is centered around the journey of twelve-year-old Aang, the current Avatar and last survivor of his nation, the Air Nomads, along with his friends Katara, Sokka, and Toph, as they strive to end the Fire Nation's war against the other nations and defeat Fire Lord Ozai before he conquers the world. It also follows the story of Zuko—the exiled prince of the Fire Nation, seeking to restore his lost honor by capturing Aang, accompanied by his uncle Iroh—and later, his sister Azula. Avatar is presented in a style that combines anime with American cartoons and relies on the imagery of primarily Chinese culture, with some other East Asian, Southeast Asian, South Asian, New World, Siberian, and Arctic influences.
Answer: In the show Avatar: The Last Airbender, Aang was the current Avatar and the last survivor of his nation, the Air Nomads. He and his friends Katara, Sokka, and Toph, strived to end the Fire Nation's war against the other nations and defeat Fire Lord Ozai before he conquered the world.
Question: Why should you workout in the morning if you work remotely ?
Answer: Working out in the morning have several benefits:
1. It gives you a purpose to wake up early in the morning.
2. It fills you with sense of accomplishment early in the day.
3. It releases dopamine and make your mood better for the whole day.
4. Helps you follow routines such as intermittent fasting and you feel energetic until afternoon till you have your fist meal.
5. You can take out 1-2 hours of time for yourself before sending time with anything else during the day.
6. There is more fat burning if you work out in the morning as body is depleted for resources and has to tap in fat reserves to provide energy for workout.
Question: which country surrounds India?
Answer: India shares borders with many countries like China, Afghanistan, and Pakistan. Bangladesh, Bhutan, Nepal, and Burma. India is also surrounded by the Bay of Bengal, the Atlantic Ocean, and the Indian Ocean.
Question: What is sourdough bread?
Answer: Sourdough bread does not use yeast to rise. Instead it uses a starter, which is fermented dough, as its rising agent. Hence it is classified as a naturally leavened bread. It normally takes longer for a sourdough bread to rise. Sourdough bread is more flavourful than normal bread. 

The starter is created using flour, salt and water. It has to be "fed" and maintained with fresh flour for the starter to remain alive. Staters can be stored in a cooler environment in order to slow down the fermentation prices.
Question: Write an argument for keeping public lands under federal control in the Intermountain West.
Answer: Public lands make up a huge proportion of the region between the crest of the Sierra Nevada and the Continental Divide in the Rockies, also known as the Intermountain West, and most of these lands are owned by the Federal government. Many residents of this sparsely populated region resent the control of these lands by distant bureaucrats whose regulations place significant restrictions on how the land is used. For this reason, movements have been ongoing for many years to work for the transfer of those lands to local authorities. While this sense of disenfranchisement is understandable, the truth is that local residents would suffer more from the loss of centralized management of these lands than they would gain through local control. This region is mostly desert, a landscape and ecosystem that is unusually vulnerable to degradation. Without the concerted efforts of an administration that can apply consistent regulation and stewardship of these lands across a broad territory that crosses state boundaries, the value of these lands to local residents would decline even further, becoming less productive and less attractive to the hunters, fishermen, and other tourists whose spending represents the majority of income for many of these Intermountain communities.
Question: Do they list all the named entity types present?
Evidence: FLOAT SELECTED: Table 2: Examples of the most frequent entities annotated in CORD-NER.
FLOAT SELECTED: Table 2: Examples of the most frequent entities annotated in CORD-NER.
Answer: No.
Question: What are the top 2 most practiced religions in Singapore?
Evidence: Most major religious denominations are present in Singapore, with the Inter-Religious Organisation, Singapore (IRO) recognising 10 major religions in the city state. A 2014 analysis by the Pew Research Center found Singapore to be the world's most religiously diverse nation.

Religion in Singapore, 2020
Religion		Percent
Buddhism	
 
31.1%
No religion	
 
20.0%
Christianity	
 
18.9%
Islam	
 
15.6%
Taoism and folk religion	
 
8.8%
Hinduism	
 
5.0%
Other religions	
 
0.6%
Buddhism is the most widely practised religion in Singapore: 31% of the resident population declared themselves adherents at the most recent census. The next-most practised religion is Christianity, followed by Islam, Taoism, and Hinduism. 20% of the population did not have a religious affiliation. The proportion of Christians, Taoists, and non-religious people increased between 2000 and 2010 by about 3 percentage points each, while the proportion of Buddhists decreased. Other faiths remained largely stable in their share of the population.

There are monasteries and Dharma centres from all three major traditions of Buddhism in Singapore: Theravada, Mahayana, and Vajrayana. Most Buddhists in Singapore are Chinese and are of the Mahayana tradition, missionaries having come into the country from China for several decades. However, Thailand's Theravada Buddhism has seen growing popularity among the populace (not only the Chinese) during the past decade. The religion of Soka Gakkai International, a Japanese Buddhist organisation, is practised by many people in Singapore, and mostly by those of Chinese descent. Tibetan Buddhism has also made slow inroads into the country in recent years.
Answer: The most widely practiced religions in Singapore are: Buddhism and Christianity at 31% and 20% respectively. However, 20% of the population did not have a religious affiliation.
Question: What is the meaning of life?
Evidence: The meaning of life, or the answer to the question: "What is the meaning of life?", pertains to the significance of living or existence in general. Many other related questions include: "Why are we here?", "What is life all about?", or "What is the purpose of existence?" There have been many proposed answers to these questions from many different cultural and ideological backgrounds. The search for life's meaning has produced much philosophical, scientific, theological, and metaphysical speculation throughout history. Different people and cultures believe different things for the answer to this question.

The meaning of life can be derived from philosophical and religious contemplation of, and scientific inquiries about existence, social ties, consciousness, and happiness. Many other issues are also involved, such as symbolic meaning, ontology, value, purpose, ethics, good and evil, free will, the existence of one or multiple gods, conceptions of God, the soul, and the afterlife. Scientific contributions focus primarily on describing related empirical facts about the universe, exploring the context and parameters concerning the "how" of life. Science also studies and can provide recommendations for the pursuit of well-being and a related conception of morality. An alternative, humanistic approach poses the question, "What is the meaning of my life?"
Answer: pertains to the significance of living or existence in general
Question: which weighs more, cold or hot water?
Answer: Cold water weighs more than hot water
Question: How large is the dataset they used?
Evidence: We need good amount of data to try deep learning state-of-the-art algorithms. There are lot of open datasets available for names, locations, organisations, but not for topics as defined in Abstract above. Also defining and inferring topics is an individual preference and there are no fix set of rules for its definition. But according to our definition, we can use wikipedia titles as our target topics. English wikipedia dataset has more than 18 million titles if we consider all versions of them till now. We had to clean up the titles to remove junk titles as wikipedia title almost contains all the words we use daily. To remove such titles, we deployed simple rules as follows -
After doing some more cleaning we were left with 10 million titles. We have a dump of 15 million English news articles published in past 4 years. Further, we reduced number of articles by removing duplicate and near similar articles. We used our pre-trained doc2vec models and cosine similarity to detect almost similar news articles. Then selected minimum articles required to cover all possible 2-grams to 5-grams. This step is done to save some training time without loosing accuracy. Do note that, in future we are planning to use whole dataset and hope to see gains in F1 and Recall further. But as per manual inspection, our dataset contains enough variations of sentences with rich vocabulary which contains names of celebrities, politicians, local authorities, national/local organisations and almost all locations, India and International, mentioned in the news text, in last 4 years.
We need good amount of data to try deep learning state-of-the-art algorithms. There are lot of open datasets available for names, locations, organisations, but not for topics as defined in Abstract above. Also defining and inferring topics is an individual preference and there are no fix set of rules for its definition. But according to our definition, we can use wikipedia titles as our target topics. English wikipedia dataset has more than 18 million titles if we consider all versions of them till now. We had to clean up the titles to remove junk titles as wikipedia title almost contains all the words we use daily. 
After doing some more cleaning we were left with 10 million titles. We have a dump of 15 million English news articles published in past 4 years. Further, we reduced number of articles by removing duplicate and near similar articles. We used our pre-trained doc2vec models and cosine similarity to detect almost similar news articles.
Answer: The answers are shown as follows:
* English wikipedia dataset has more than 18 million
* a dump of 15 million English news articles
Question: Which geographical regions correlate to the trend?
Evidence: Observing the results of the linear regression in Table 2, we find the normalized governmental reported cases count and regional feature to be statistically significant on the sexual harassment rate in the Twitter data ($p-value<0.05$). Specifically, the change in the number of reported cases constitutes a considerable change in the number of #MeToo users on Twitter as p-value is extremely small at $5.7e-13$. This corresponds to the research by Napolitano (2014) regarding the "Yes means yes" movement in higher education institutes in recent years, as even with some limitations and inconsistency, the sexual assault reporting system is gradually becoming more rigorous BIBREF17. Meanwhile, attending colleges in the Northeast, West and South regions increases the possibility of posting about sexual harassment (positive coefficients), over the Midwest region. This finding is interesting and warrants further scrutiny.
Meanwhile, attending colleges in the Northeast, West and South regions increases the possibility of posting about sexual harassment (positive coefficients), over the Midwest region. 
Answer: Northeast U.S., West U.S. and South U.S.
Question: When looking to purchase a bicycle, you need to understand a number of factors. These include the primary use of the bicycle being either for transportation or pleasure. When choosing a bicycle for transportation you want to factor in cost, weight and durability. When choosing a bicycle for pleasure, comfort is the main factor.
Answer: As part of the buying process, getting expert opinions will be helpful. You want to discuss your purchase with people who have made a similar purchase so that you can make an educated decision.
Question: What are the difficulties in developing a dialogue system?
Evidence: The obvious difficulty when developing a dialog system is finding a way how to identify the piece of information that the user is interested in. This is especially a problem for dialog systems based on knowledge graphs containing a large amount of complex structured information. While a similar problem is being solved in a task of question answering, dialog systems have more possibilities of identifying the real intention of the user. For example, a dialog system can ask for additional information during the dialog.
We distinguish three different basic approaches to requesting knowledge bases:
A combination of the above approaches is also possible. For example, we can imagine scenarios where the dialog system starts with hand-crafted rules, which are subsequently interactively improved through dialogs with its users. With a growing demand for open domain dialog systems, it shows that creating hand-crafted policies does not scale well - therefore, machine learning approaches are gaining on popularity. Many public datasets for offline learning have been published BIBREF8 , BIBREF7 . However, to our knowledge, no public datasets for interactive learning are available. To fill this gap, we collected a dataset which enables to train interactively learned policies through a simulated interaction with users.
The obvious difficulty when developing a dialog system is finding a way how to identify the piece of information that the user is interested in.
Answer: The obvious difficulty when developing a dialog system is finding a way how to identify the piece of information that the user is interested in.
Question: What are the only three ingredients to make authentic Chantilly cream?
Answer: Cream (containing at least 30% fat), icing sugar, and vanilla
Question: From the passage provided, extract the gross earnings of the movie Iron Man
Evidence: Iron Man premiered in Sydney on April 14, 2008, and was released in the United States on May 2, being the first film in Phase One of the MCU. It grossed over $585 million, becoming the eighth-highest grossing film of 2008. The film received praise from critics, especially for Downey's performance, as well as Favreau's direction, visual effects, action sequences, and writing. It was selected by the American Film Institute as one of the ten best films of 2008, received two nominations at the 81st Academy Awards for Best Sound Editing and Best Visual Effects. In 2022, the film was selected for preservation in the United States National Film Registry by the Library of Congress as being "culturally, historically, or aesthetically significant". Two sequels have been released: Iron Man 2 (2010) and Iron Man 3 (2013).
Answer: over $585 million
Question: Using examples from the text, list some popular songs from the album For Bitter or Worse.
Evidence: For Bitter or Worse is the sixth studio album from the Dutch singer Anouk. The album was released on 18 September 2009, via the record label EMI.

The first single from the album, "Three Days in a Row" was released in August. It reached the top of the Netherlands charts in September 2009, making it Anouk's first number one in the country. In June of the same year, one of the songs recorded for the album, "Today", was released as promo material. It was so successful that, despite never being released as an official single, the song reached number 50 in the Dutch chart. The second single Woman, was sent to radio stations at the end of October 2009. After just one day the single was at number one on airplay chart. The single was released physically on 24 November 2009.
Answer: Popular songs from the album For Bitter or Worse include "Three Days in a Row" and "Today".
Question: What's the meaning of skipping proportion in corroborating sentence-level metrics in Eye-tracking validation?
Evidence: The aim of the technical validation of the data is to guarantee good recording quality and to replicate findings of previous studies investigating co-registration of EEG and eye movement data during natural reading tasks (e.g. dimigen2011coregistration). We also compare the results to ZuCo 1.0 BIBREF1, which allows a more direct comparison due to the analogous recording procedure.
Moreover, we corroborated these sentence-level metrics by visualizing the skipping proportion on word level (Figure 4). The skipping proportion is the average rate of words being skipped (i.e. not being fixated) in a sentence. As expected, this also increases in the task-specific reading.
Answer: It is the average rate of words being skipped (i.e. not being fixated) in a sentence.
Question: Who was Charles Stuart, Duke of Cambridge
Evidence: Charles Stuart (22 October 1660 – 5 May 1661) was the first of four sons and eight children born from the marriage between the Duke of York (later King James II of England & VII of Scotland) and his first wife, Anne Hyde. He was styled Duke of Cambridge, but never formally created so, because he died so young.

Charles was conceived seven months before his parents' official marriage and if royal advisors and Queen Henrietta Maria, the mother of James, had their way, he could have been declared illegitimate. King Charles II, James's older brother, approved of the marriage and the wedding between James and Anne was held on 3 September 1660 in London. Charles was born on 22 October and was baptised on 1 January 1661 at Worcester House. However, he died before reaching the age of one, after becoming ill with smallpox. He was buried in Westminster Abbey on 6 May 1661. Three of his younger brothers, likewise short-lived, were also called Duke of Cambridge: James, Edgar, and Charles.

Arms
See adjacent text
Coat of arms as Duke of Cambridge
During his short life, Charles bore a coat of arms, as a grandson of a British sovereign, consisting those of the kingdom, differenced by a label argent of five points ermine.
Answer: Charles Stuart (22 October 1660 – 5 May 1661) was the first of four sons and eight children born from the marriage between the Duke of York (later King James II of England & VII of Scotland) and his first wife, Anne Hyde. He was styled Duke of Cambridge, but never formally created so, because he died so young.

Charles was conceived seven months before his parents' official marriage and if royal advisors and Queen Henrietta Maria, the mother of James, had their way, he could have been declared illegitimate. King Charles II, James's older brother, approved of the marriage and the wedding between James and Anne was held on 3 September 1660 in London. Charles was born on 22 October and was baptised on 1 January 1661 at Worcester House. However, he died before reaching the age of one, after becoming ill with smallpox. He was buried in Westminster Abbey on 6 May 1661. Three of his younger brothers, likewise short-lived, were also called Duke of Cambridge: James, Edgar, and Charles.

During his short life, Charles bore a coat of arms, as a grandson of a British sovereign, consisting those of the kingdom, differenced by a label argent of five points ermine.
Question: What literary technique is used in the phrase “simmered on a smooth summer sidewalk”?
Answer: “Simmered on a smooth summer sidewalk” is an example of alliteration, which is a literary technique often used to emphasize a phrase or make a phrase stand out more to a reader.
Question: Why can camels survive for long without water?
Answer: Camels use the fat in their humps to keep them filled with energy and hydration for long periods of time.
Question: What color is the Lethata dispersa?
Evidence: Lethata dispersa is a moth of the family Depressariidae. It is found in Brazil (Matto Grosso)

The wingspan is about 23 mm. The forewings are yellow with the costa rosy and the dorsum narrowly edged brown and with a faint spot in the fold brown. There is a spot at the end of the cell consisting of a ring of brown enclosing a whitish spot. There is an oblique brown line extending from the costa at near the midpoint through a spot at the end of the cell to the tornus. The terminal line is brown. The hindwings are grey.
Answer: Lethata dispersa is a moth with a variety of different colors. It has yellow forewings, grey hindwings, and features brown at the dorsum, with a ring of brown enclosing a white spot.
Question: In what year was Peter born?  Use roman numerals.
Evidence: Peter Jordan (born 26 April 1967) is a German actor. He appeared in more than seventy films since 1995.
Answer: MCMLXVII