DataHammer/scimrc huggingface dataset:
Question: From this summary of how Bilbo found the Ring in The Hobbit, how did Bilbo beat Gollum at the Riddle game?
Evidence: As told in The Hobbit, Bilbo found the Ring while lost in the tunnels near Gollum's lair. In the first edition, Gollum offers to surrender the Ring to Bilbo as a reward for winning the Riddle Game. When Tolkien was writing The Lord of the Rings, he realized that the Ring's grip on Gollum would never permit him to give it up willingly. He therefore revised The Hobbit: in the second edition, after losing the Riddle Game to Bilbo, Gollum went to get his "Precious" to help him kill and eat Bilbo, but found the Ring missing. Deducing from Bilbo's last question—"What have I got in my pocket?"—that Bilbo had found the Ring, Gollum chased him through the caves, not realizing that Bilbo had discovered the Ring's power of invisibility and was following him to the cave's mouth. Bilbo escaped Gollum and the goblins by remaining invisible, but he chose not to tell Gandalf and the dwarves that the Ring had made him invisible. Instead he told them a story that followed the first edition: that Gollum had given him the Ring and shown him the way out. Gandalf was immediately suspicious of the Ring, and later forced the real story from Bilbo.
Answer: Gollum was unable to answer Bilbo's last question, "What have I got in my pocket?".
Question: Write a short, polite but forceful letter to the City of Toronto requesting they waive their assessed penalty for late submission of the annual home vacancy declaration, which was impossible to file due to an overwhelmed web portal and incorrect backend data for my home.
Answer: To Whom It May Concern:  I was unable to complete the filing of my home vacancy declaration by the deadline, and was assessed a penalty for the late submission. I faced numerous problems during submission due to your overwhelmed web portal, and even once I passed that barrier, I then faced incorrect data about my account that made it impossible to complete the process.  I would appreciate if you would waive the assessed penalty due to these circumstances.  I sympathesize with the difficulties you faced with the roll out of this system, and look forward to what will surely be a smoother process next year.  Sincerely, Signed.
Question: What was previous state of the art model?
Evidence: We first compared the performance of Transformer Transducer (T-T) models with full attention on audio to an RNN-T model using a bidirectional LSTM audio encoder. As shown in Table TABREF12, the T-T model significantly outperforms the LSTM-based RNN-T baseline. We also observed that T-T models can achieve competitive recognition accuracy with existing wordpiece-based end-to-end models with similar model size. To compare with systems using shallow fusion BIBREF18, BIBREF25 with separately trained LMs, we also trained a Transformer-based LM with the same architecture as the label encoder used in T-T, using the full 810M word token dataset. This Transformer LM (6 layers; 57M parameters) had a perplexity of $2.49$ on the dev-clean set; the use of dropout, and of larger models, did not improve either perplexity or WER. Shallow fusion was then performed using that LM and both the trained T-T system and the trained bidirectional LSTM-based RNN-T baseline, with scaling factors on the LM output and on the non-blank symbol sequence length tuned on the LibriSpeech dev sets. The results are shown in Table TABREF12 in the “With LM” column. The shallow fusion result for the T-T system is competitive with corresponding results for top-performing existing systems.
As shown in Table TABREF12, the T-T model significantly outperforms the LSTM-based RNN-T baseline.
Answer: The answers are shown as follows:
* LSTM-based RNN-T
Question: Why are iPhones more popular than Android phones inside the United States, while the opposite is true outside the United States?
Answer: The primary reason why iPhones are more popular inside the United States than outside the United States is cost. Because many companies manufacture and sell Android phones, the cost of an Android phone is low. On the other hand, Apple is the only company that sells iPhones, and this lack of competition allows Apple to charge a higher price. The United States has the highest per capita household income of any country in the world, thus people in the United States are more able to afford iPhones than are people outside the United States. A secondary reason for iPhone’s relative popularity in the United States is cultural: an iPhone is seen as a sort of status symbol, and some iPhone features only work with other iPhones, thus some people feel they will be “missing out” socially if they have an Android phone instead of an iPhone.
Question: What is 'karma' according to Buddhism?
Answer: Karma is a central and fundamental aspect of Buddhist doctrine common to all traditions of Buddhism. The Buddhist concept of Karma is a natural process that operates with all our volitional actions and which does not need an external agency or power that sits in judgement.

Karma in Buddhism should not be considered as moral justice, or a method of reward and punishment, that needs an external body or authority to decide whom or what should be punished and rewarded. It is believed that Gautama Buddha attained complete insight into how the process of Karma works during the night of his full enlightenment when, through the divine eye (dibbacakku), Buddha saw how other beings die and are reborn in happy and unhappy states according to their Karma.

According to the Cula-kammavibhanga sutta of the Majima Nikava (collection of the middle length discourses of the Buddha), a young brahmin by the name of Subha had approached the Buddha and inquired as to why there was so much inequality among human beings in terms of being short-lived or long-lived, sickly or healthy, ugly or beautiful, powerful or powerless, poor or rich, low-born or high-born, ignorant or intelligent, etc. Buddha had then explained that:
"all living beings are the owners of their actions, heirs to their actions, they originate from their actions, they are related through their actions, they have their actions as their refuge and that it is action or Karma that distinguishes beings as inferior and superior

The word Karma in Pali, and karma in Sanskrit, means action but encompasses only actions that are intentional, volitional and willful and which will lead to consequences sooner or later. The mind (citta) by itself cannot perform or direct any mental, verbal or physical action and it is the intention, will, mental effort or volition (cetana) that directs any mental, verbal or physical action.

Thus the Buddha declared:
"Cetanaham bhikkhave kammam vadami
Cetayitva kammam karoti, kayena, vacaya, manasa"

"It is volition that I call Karma, by volition one performs Karma through body, word or mind."
Question: From the passage provided, extract the year  Indian National Congress was founded
Evidence: The Indian National Congress (INC), colloquially the Congress Party but often simply the Congress, is a political party in India with widespread roots. Founded in 1885, it was the first modern nationalist movement to emerge in the British Empire in Asia and Africa. From the late 19th century, and especially after 1920, under the leadership of Mahatma Gandhi, the Congress became the principal leader of the Indian independence movement. The Congress led India to independence from the United Kingdom,[d
Answer: Indian National Congress was founded in 1885
Question: I have wine tasting plans for the weekend , give me some tips so that I look like an expert
Answer: The most important part of Wine tasting is to enjoy it and have fun. There are five important steps to tasting wine which are described below.

See the Color  - Take a look at the color of the wine you are about to taste, it will give you a good indication on the age of the wine. Young white wines are clear and look like water, while older wines that have been aged in oak get a gold tint. Young red wines are vivid purplish red while older wines have brownish tones. 
Swirl the wine - Swirling the wine helps to expose the wine to more oxygen and release its aroma, this is called as aerating the wine. Watch how the wine runs down the glass. If the streaks of wine are thick and run relatively slow the wine has more sugar or alcohol. If the wine is thin and runs down the glass fast it has less alcohol. 
Smell the wine - After you swirl the wine take a sniff and it will smell much more vibrant. There are three types of aromas that wines have: primary are  fruity or floral, secondary ones come from aging in the barrels and tertiary are aging signs.
Sip the wine - Take a sip of the wine and spread it around your mouth to detect the different type of taste it provides. The tip of the tongue will give you the sweetness while the sides give you a good indication of sourness or acidity. 
Savor the wine- How does the wine feel after. Does it leave a bitterness or leathery feel on your tongue, it means the wine has more tannins.Does the wine feel light or dense , will give you a sense of whether it is light or medium bodied. 

After you have gone through the steps the most important thing is if you liked the wine. Take notes after each taste and you will eventually find out the type of wines you like.
Question: Think up ways to clean a keyboard.
Answer: Some ways to clean a keyboard: use a compressed air can to blow out dust, manually take off each key cap using a specialized key tool and wash them in soap and water, use a dusting brush that is designed for fitting in the keyboard grooves, use an antistatic dusting wipe.
Question: Tell me whether these are fiction or non fiction books: "To Kill a Mocking Bird", "The Lord of the Rings", "A Brief History of Time".
Answer: "To Kill a Mocking Bird", "The Lord of the Rings" are fictions. "A Brief History of Time" is non fiction.
Question: Who is the Patron Saint of Ireland?
Answer: St. Patrick is Ireland's main patron saint and on March 17, the world celebrates the feast day of St. Patrick, a zealous, fifth-century British bishop who became famous for spreading Christianity in Ireland.
Question: What is kombucha?
Answer: Kombucha is a fermented tea that is often fizzy or carbonated, and a bit sour. Kombucha typically has a low concentration of alcohol, however some kombucha can be made with higher levels of alcohol content. Kombucha is fermented for a number of days and then bottled with various flavor enhancing ingredients such as syrups, herbs, juices or fruit. Kombucha can be made by brewers at home with basic ingredients and materials, and it can also be mass produced. Kombucha is made from the combination of typically black tea, sugar, and a SCOBY aka a symbiotic culture of bacteria and yeast.
Question: Do they report results only on English datasets?
Evidence: Using the Twitter Application Program Interface (API) and the IUNI OSoMeBIBREF46 (a service which provides searchable access to the Twitter “Gardenhose”, a 10% sample of all daily tweets), we search for tweets that matched both “diagnos*” and “depress*.” The resulting set of tweets are then filtered for matching the expressions “i”, “diagnos*”, “depres*” in that order in a case-insensitive manner allowing insertions to match the greatest variety of diagnosis statements, e.g. a tweet that states “I was in fact just diagnosed with clinical depression” would match. Finally, to ensure we are only including true self-referential statements of a depression diagnosis, a team of 3 experts manually removed quotes, jokes, and external references. For each qualifying diagnosis tweet we retrieve the timeline of the corresponding Twitter user using the Twitter user_timeline API endpoint . Subsequently, we remove all non-English tweets (Twitter API machine-detected“lang” field), all retweets, and tweets that contain “diagnos*” or “depress*”, but not a valid diagnosis statement. The resulting Depressed cohort contains 1,207 individuals and 1,759,644 tweets ranging from from May 2008 to September 2018.
For each qualifying diagnosis tweet we retrieve the timeline of the corresponding Twitter user using the Twitter user_timeline API endpoint . Subsequently, we remove all non-English tweets (Twitter API machine-detected“lang” field), all retweets, and tweets that contain “diagnos*” or “depress*”, but not a valid diagnosis statement. The resulting Depressed cohort contains 1,207 individuals and 1,759,644 tweets ranging from from May 2008 to September 2018.
Answer: Yes.
Question: Which characters belong to DC or Marvel Universe? Boomerang, Captain Boomerang
Answer: Boomerang is Marvel, Captain Boomerang is DC
Question: Extract the names of the Formula One teams Hamilton was a part of from the text. Separate them with a comma.
Evidence: Born and raised in Stevenage, Hertfordshire, Hamilton joined the McLaren young driver programme in 1998 at the age of 13, becoming the youngest racing driver ever to be contracted by a Formula One team. This led to a Formula One drive with McLaren for six years from 2007 to 2012, making Hamilton the first ever black driver to race in the series. In his inaugural season, Hamilton set numerous records as he finished runner-up to Kimi Räikkönen by one point. The following season, he won his maiden title in dramatic fashion—making a crucial overtake at the last corner on the last lap of the last race of the season—to become the then-youngest Formula One World Champion in history. After six years with McLaren, Hamilton signed with Mercedes in 2013.
Answer: McLaren, Mercedes
Question: What difficulty is existing in estimating the probability using sense–tagging?
Evidence: The information content of a concept may be derived from a corpus (corpus–based) or directly from a taxonomy (intrinsic–based). In this work we focus on corpus–based techniques.
For corpus–based information content, we estimate the probability of a concept INLINEFORM0 by taking the sum of the probability of the concept INLINEFORM1 and the probability its descendants INLINEFORM2 (Equation EQREF16 ). DISPLAYFORM0 
The initial probabilities of a concept ( INLINEFORM0 ) and its descendants ( INLINEFORM1 ) are obtained by dividing the number of times each concept and descendant occurs in the corpus, and dividing that by the total numbers of concepts ( INLINEFORM2 ).
Ideally the corpus from which we are estimating the probabilities of concepts will be sense–tagged. However, sense–tagging is a challenging problem in its own right, and it is not always possible to carry out reliably on larger amounts of text. In fact in this paper we did not use any sense–tagging of the corpus we derived information content from.
Instead, we estimated the probability of a concept by using the UMLSonMedline dataset. This was created by the National Library of Medicine and consists of concepts from the 2009AB UMLS and the counts of the number of times they occurred in a snapshot of Medline taken on 12 January, 2009. These counts were obtained by using the Essie Search Engine BIBREF14 which queried Medline with normalized strings from the 2009AB MRCONSO table in the UMLS. The frequency of a CUI was obtained by aggregating the frequency counts of the terms associated with the CUI to provide a rough estimate of its frequency. The information content measures then use this information to calculate the probability of a concept.
Another alternative is the use of Intrinsic Information Content. It assess the informativeness of concept based on its placement within a taxonomy by considering the number of incoming (ancestors) relative to outgoing (descendant) links BIBREF15 (Equation EQREF17 ). DISPLAYFORM0 
where INLINEFORM0 are the number of descendants of concept INLINEFORM1 that are leaf nodes, INLINEFORM2 are the number of concept INLINEFORM3 's ancestors and INLINEFORM4 are the total number of leaf nodes in the taxonomy.
However, sense–tagging is a challenging problem in its own right, and it is not always possible to carry out reliably on larger amounts of text.
Answer: Sense–tagging is a challenging problem in its own right, and it is not always possible to carry out reliably on larger amounts of text.
Question: Tell me some point by point details about Art Deco using given text as a reference
Evidence: Art Deco, short for the French Arts Décoratifs, and sometimes just called Deco, is a style of visual arts, architecture, and product design, that first appeared in France in the 1910s (just before World War I), and flourished in the United States and Europe during the 1920s and 1930s. Through styling and design of the exterior and interior of anything from large structures to small objects, including how people look (clothing, fashion and jewelry), Art Deco has influenced bridges, buildings (from skyscrapers to cinemas), ships, ocean liners, trains, cars, trucks, buses, furniture, and everyday objects like radios and vacuum cleaners.
Answer: 1.	A style of visual arts, architecture, and product design, Art Deco—short for the French Arts Décoratifs—first debuted in France in the 1910s, soon before World War I, and flourished in the United States and Europe in the 1920s and 1930s.  
2.	Art Deco has influenced bridges, buildings (from skyscrapers to cinemas), ships, ocean liners, trains, cars, trucks, buses, furniture, and common household items like radios and vacuum cleaners.
3.	Art Deco has also influenced styling and design of the exterior and interior of anything from large structures to small objects, as well as how people look (clothing, fashion, and jewellery).
Question: What country is the newest member of NATO?
Answer: Finland became the 31st member on April 4, 2023
Question: What registers did the authors choose?
Evidence: As a main field of interest in the current study, we chose controversies in education. One distinguishing feature of educational topics is their breadth of sub-topics and points of view, as they attract researchers, practitioners, parents, students, or policy-makers. We assume that this diversity leads to the linguistic variability of the education topics and thus represents a challenge for NLP. In a cooperation with researchers from the German Institute for International Educational Research we identified the following current controversial topics in education in English-speaking countries: (1) homeschooling, (2) public versus private schools, (3) redshirting — intentionally delaying the entry of an age-eligible child into kindergarten, allowing their child more time to mature emotionally and physically BIBREF51 , (4) prayer in schools — whether prayer in schools should be allowed and taken as a part of education or banned completely, (5) single-sex education — single-sex classes (males and females separate) versus mixed-sex classes (“co-ed”), and (6) mainstreaming — including children with special needs into regular classes.
Since we were also interested in whether argumentation differs across registers, we included four different registers — namely (1) user comments to newswire articles or to blog posts, (2) posts in discussion forums (forum posts), (3) blog posts, and (4) newswire articles. Throughout this work, we will refer to each article, blog post, comment, or forum posts as a document. This variety of sources covers mainly user-generated content except newswire articles which are written by professionals and undergo an editing procedure by the publisher. Since many publishers also host blog-like sections on their portals, we consider as blog posts all content that is hosted on personal blogs or clearly belong to a blog category within a newswire portal.
Because we were also interested in whether argumentation differs across registers,10 we included four different registers, namely, (1) user comments to newswire articles or to blog posts; (2) posts in discussion forums (forum posts); (3) blog posts; and (4) newswire articles.
Answer: (1) user comments to newswire articles or to blog posts; (2) posts in discussion forums (forum posts); (3) blog posts; and (4) newswire articles.
Question: What does the paper estimate?
Evidence: Indicating that a web page is controversial, or disputed - for example, in a search result - facilitates an educated consumption of the information therein, suggesting the content may not represent the “full picture”. Here, we consider the problem of estimating the level of controversiality associated with a given Wikipedia concept (title). We demonstrate that the textual contexts in which the concept is referenced can be leveraged to facilitate this.
The definition of which concepts are controversial is controversial by itself; an accurate definition of this elusive notion attracted the attention of researchers from various fields, see for example some recent attempts in BIBREF0, BIBREF1, BIBREF2.
Most people would agree, for example, that Global warming is a controversial concept, whereas Summer is not. However, the concept Pollution may be seen as neutral by some, yet controversial by others, who associate it with environmental debates. In other words, different people may have different opinions, potentially driven by different contexts salient in their mind. Yet, as reported in the sequel, an appreciable level of agreement can be reached, even without explicit context.
Focusing here on Wikipedia concepts, we adopt as an initial “ground truth” the titles listed on the Wikipedia list of controversial issues, which is curated based on so-called “edit wars”. We then manually annotate a set of Wikipedia titles which are locked for editing, and evaluate our system on this much larger and more challenging dataset.
To estimate the level of controversy associated with a Wikipedia concept, we propose to simply examine the words in the sentences in which the concept is referenced. Because a concept can often be found in multiple contexts, the estimation can be seen as reflecting the “general opinion” about it in the corpus. This contrasts previous works, which consider this a binary problem, and employ a complex combination of features extracted from Wikipedia's article contents and inter-references, and more extensively – from the rich edit history thereof.
Here, we consider the problem of estimating the level of controversiality associated with a given Wikipedia concept (title).
Answer: The level of controversiality associated with a given Wikipedia concept.
Question: What is the difference between race and ethnicity?
Answer: Race is a combination of cultural, physical and behavioral attributes whereas ethnicity is recognized by shared cultures and language.
Question: What is it like living in the Pacific Northwest?
Answer: The Pacific Northwest is comprised of U.S. states of Oregon, Washington, and Idaho, and the Canadian province of British Columbia - and sometimes Alaska is included. The Pacific Northwest, also referred to as PNW, it a diverse area with mountains, the pacific ocean, lakes, islands, volcanoes, deserts and rainforests. It is one of the most diverse climates in the United States. People who live here love the outdoors and the beauty.