DataHammer/scimrc huggingface dataset:
Question: Did they propose other metrics?
Evidence: We introduce our proposed diversity, density, and homogeneity metrics with their detailed formulations and key intuitions.
We introduce our proposed diversity, density, and homogeneity metrics with their detailed formulations and key intuitions.
Answer: Yes.
Question: Are there still grizzly bears in California?
Answer: No, although the grizzly bear is a symbol of California, grizzly bears are extinct in California
Question: How many techniques does the authors' corpus uses annotated on the same set of news articles?
Evidence: Propaganda has been tackled mostly at the article level. BIBREF3 created a corpus of news articles labelled as propaganda, trusted, hoax, or satire. BIBREF4 experimented with a binarized version of that corpus: propaganda vs. the other three categories. BIBREF5 annotated a large binary corpus of propagandist vs. non-propagandist articles and proposed a feature-based system for discriminating between them. In all these cases, the labels were obtained using distant supervision, assuming that all articles from a given news outlet share the label of that outlet, which inevitably introduces noise BIBREF6.
A related field is that of computational argumentation which, among others, deals with some logical fallacies related to propaganda. BIBREF7 presented a corpus of Web forum discussions with instances of ad hominem fallacy. BIBREF8, BIBREF9 introduced Argotario, a game to educate people to recognize and create fallacies, a by-product of which is a corpus with $1.3k$ arguments annotated with five fallacies such as ad hominem, red herring and irrelevant authority, which directly relate to propaganda.
Unlike BIBREF8, BIBREF9, BIBREF7, our corpus uses 18 techniques annotated on the same set of news articles. Moreover, our annotations aim at identifying the minimal fragments related to a technique instead of flagging entire arguments.
The most relevant related work is our own, which is published in parallel to this paper at EMNLP-IJCNLP 2019 BIBREF10 and describes a corpus that is a subset of the one used for this shared task.
Unlike , our corpus uses 18 techniques annotated on the same set of news articles.
Answer: 18 techniques.
Question: What is I Liq Chuan?
Evidence: Sam F.S. Chin (Chin Fan Siong, 曾帆祥, born August 1, 1954) is the Grandmaster and Gatekeeper of the martial art called I Liq Chuan, and also known as "the Martial Art of Awareness". Chin developed the grading system for this system.

Chin was trained since childhood by his father, Chin Lik Keong, founder of I Liq Chuan, and in 1978, he won the state heavy weight kickboxing championships of Selangor (Malaysia). In August 2009 Chin was officially named the Gate Keeper and Lineage Holder of the I Liq Chuan. He is also the founder and President of Chin Family I Liq Chuan Association that supports the martial art's growth.

Chin has taught workshops worldwide , written two books on his family's martial art, co-authored articles, and produced a series of DVDs. Chin was interviewed by Jess O'Brien for his 2007 book "Nei Jia Quan: Internal Martial Arts".

In August 2009, Chin was also recognized by the USA Wushu Kung-Fu Federation as a Hall of Fame Outstanding Master. In 2014, he was written about by Ashe Higgs in Kung Fu Tai Chi Magazine "Finding the Center: I Liq Chuan’s Three Essential Qualities for Offense and Defense as One". Chin was also the subject of the 2016 CCTV Documentary "Kung Fu Abroad: I Liq Chuan 中央电视台《功夫在外》纪录片".

On November 15, 2017 Sam Chin became an honorary professor at the University of Plovdiv, Bulgaria in recognition of his lifetime of achievement in spreading I Liq Chuan.
Answer: I Liq Chuan is a style of martial art founded by Chin Lik Keong from Malaysia that is also known as the "Martial Art of Awareness".
Question: Is the Counterfactual Data Augmentation (CDA) able to mitigate indirect bias?
Evidence: Gender bias describes an inherent prejudice against a gender, captured both by individuals and larger social systems. Word embeddings, a popular machine-learnt semantic space, have been shown to retain gender bias present in corpora used to train them BIBREF0. This results in gender-stereotypical vector analogies à la NIPS20135021, such as man:computer programmer :: woman:homemaker BIBREF1, and such bias has been shown to materialise in a variety of downstream tasks, e.g. coreference resolution BIBREF2, BIBREF3.
By operationalising gender bias in word embeddings as a linear subspace, DBLP:conf/nips/BolukbasiCZSK16 are able to debias with simple techniques from linear algebra. Their method successfully mitigates [author=simone,color=blue!40,size=,fancyline,caption=,]does not particularly like boldfacing for emphasis, but can live with.direct bias: man is no longer more similar to computer programmer in vector space than woman. However, the structure of gender bias in vector space remains largely intact, and the new vectors still evince indirect bias: associations which result from gender bias between not explicitly gendered words, for example a possible association between football and business resulting from their mutual association with explicitly masculine words BIBREF4. In this paper we continue the work of BIBREF4, and show that another paradigm for gender bias mitigation proposed by BIBREF5, Counterfactual Data Augmentation (CDA), is also unable to mitigate indirect bias. We also show, using a new test we describe (non-biased gender analogies), that WED might be removing too much gender information, casting further doubt on its operationalisation of gender bias as a linear subspace.
To improve CDA we make two proposals. The first, Counterfactual Data Substitution (CDS), is designed to avoid text duplication in favour of substitution. The second, the Names Intervention, is a method which can be applied to either CDA or CDS, and treats bias inherent in first names. It does so using a novel name pairing strategy that accounts for both name frequency and gender-specificity. Using our improvements, the clusters of the most biased words exhibit a reduction of cluster purity by an average of 49% across both corpora following treatment, thereby offering a partial solution to the problem of indirect bias as formalised by BIBREF4. [author=simone,color=blue!40,size=,fancyline,caption=,]first part of reaction to reviewer 4Additionally, although one could expect that the debiased embeddings might suffer performance losses in computational linguistic tasks, our embeddings remain useful for at least two such tasks, word similarity and sentiment classification BIBREF6.
In this paper we continue the work of BIBREF4, and show that another paradigm for gender bias mitigation proposed by BIBREF5, Counterfactual Data Augmentation (CDA), is also unable to mitigate indirect bias.
Answer: No, it is not able.
Question: Extract the factors that influence the cost of building a house
Evidence: The cost of building a house varies by country widely. According to data from the National Association of Realtors, the median cost of buying an existing single-family house in the United States is $274,600, whereas the average cost to build is $296,652. Several different factors can impact the cost of building a house, including the size of the dwelling, the location, and availability of resources, the slope of the land, the quality of the fixtures and fittings, and the difficulty in finding construction and building materials talent
Answer: The factors that influence the cost of building a house are, the size of the dwelling, the location, and availability of resources, the slope of the land, the quality of the fixtures and fittings, and the difficulty in finding construction and building materials talent
Question: Of the following book characters, which are vampires: Lestat de Lioncourt, Bella Swan, Edward Cullen, Jacob Black, The Seeker
Answer: Lestat de Lioncourt, Bella Swan, Edward Cullen
Question: Give me a list of benefits of swimming
Answer: Swimming has many benefits that help promote both mental and physical wellness. Mentally, swimming is great for clearing your mind and actually has been proven to release  endorphins throughout your body, providing a refreshing and happy feeling post a workout. Physically, swimming is an excellent way to gain cardio fitness, while also building strength and flexibility at any age.
Question: Who is Jorge Luis Borges?
Evidence: Jorge Francisco Isidoro Luis Borges Acevedo (/ˈbɔːrhɛs/; Spanish: [ˈboɾxes] (listen); 24 August 1899 – 14 June 1986) was an Argentine short-story writer, essayist, poet and translator, as well as a key figure in Spanish-language and international literature. His best-known books, Ficciones (Fictions) and El Aleph (The Aleph), published in the 1940s, are collections of short stories exploring themes of dreams, labyrinths, chance, infinity, archives, mirrors, fictional writers and mythology. Borges's works have contributed to philosophical literature and the fantasy genre, and have had a major influence on the magic realist movement in 20th century Latin American literature.
Answer: Jorge Francisco Isidoro Luis Borges Acevedo (/ˈbɔːrhɛs/; Spanish: [ˈboɾxes] (listen); 24 August 1899 – 14 June 1986) was an Argentine short-story writer, essayist, poet and translator, as well as a key figure in Spanish-language and international literature. His best-known books, Ficciones (Fictions) and El Aleph (The Aleph), published in the 1940s, are collections of short stories exploring themes of dreams, labyrinths, chance, infinity, archives, mirrors, fictional writers and mythology. Borges's works have contributed to philosophical literature and the fantasy genre, and have had a major influence on the magic realist movement in 20th century Latin American literature.

Born in Buenos Aires, Borges later moved with his family to Switzerland in 1914, where he studied at the Collège de Genève. The family travelled widely in Europe, including Spain. On his return to Argentina in 1921, Borges began publishing his poems and essays in surrealist literary journals. He also worked as a librarian and public lecturer. In 1955, he was appointed director of the National Public Library and professor of English Literature at the University of Buenos Aires. He became completely blind by the age of 55. Scholars have suggested that his progressive blindness helped him to create innovative literary symbols through imagination.[Note 1] By the 1960s, his work was translated and published widely in the United States and Europe. Borges himself was fluent in several languages.

In 1961, he came to international attention when he received the first Formentor Prize, which he shared with Samuel Beckett. In 1971, he won the Jerusalem Prize. His international reputation was consolidated in the 1960s, aided by the growing number of English translations, the Latin American Boom, and by the success of García Márquez's One Hundred Years of Solitude. He dedicated his final work, The Conspirators, to the city of Geneva, Switzerland. Writer and essayist J. M. Coetzee said of him: "He, more than anyone, renovated the language of fiction and thus opened the way to a remarkable generation of Spanish-American novelists."
Question: How do they gather data for the query explanation problem?
Evidence: WikiTableQuestions BIBREF1 is a question answering dataset over semi-structured tables. It is comprised of question-answer pairs on HTML tables, and was constructed by selecting data tables from Wikipedia that contained at least 8 rows and 5 columns. Amazon Mechanical Turk workers were then tasked with writing trivia questions about each table. In contrast to common NLIDB benchmarks BIBREF2 , BIBREF0 , BIBREF15 , WikiTableQuestions contains 22,033 questions and is an order of magnitude larger than previous state-of-the-art datasets. Its questions were not designed by predefined templates but were hand crafted by users, demonstrating high linguistic variance. Compared to previous datasets on knowledge bases it covers nearly 4,000 unique column headers, containing far more relations than closed domain datasets BIBREF15 , BIBREF2 and datasets for querying knowledge bases BIBREF16 . Its questions cover a wide range of domains, requiring operations such as table lookup, aggregation, superlatives (argmax, argmin), arithmetic operations, joins and unions. The complexity of its questions can be shown in Tables TABREF6 and TABREF66 .
WikiTableQuestions contains 22,033 questions and is an order of magnitude larger than previous state-of-the-art datasets. Its questions were not designed by predefined templates but were hand crafted by users, demonstrating high linguistic variance.
Answer: The answers are shown as follows:
* hand crafted by users
Question: Given this mechanism that the Tesla Model Y car uses to heat the interior cabin, what are some pros and cons of this design?
Evidence: The Model Y is Tesla's first car to use a heat pump instead of electric resistance for interior cabin heating. Some electric vehicles from other manufacturers, including the Nissan Leaf, Renault Zoe, BMW i3 EV, Jaguar I-Pace, Audi e-tron, and Kia Niro, had already implemented heat pumps. In cold weather, the Model Y heat pump can be up to 300% more efficient than other Tesla cars' use of electric resistance heating. Because of this, the Model Y should be more energy efficient than other Tesla cars in cold weather. Electric cars can lose 40% or more of their range in cold weather (at ambient temperatures below 20 °F (−7 °C)) when heating the interior cabin.
Answer: The heat pump in the Tesla Model Y runs the same heating operations as other cars but much more efficiently, significantly increasing driving range for the same battery size. Most other cars use electric resistance heating which consumes much more energy to perform the same job.
Question: What is the Great Emu War and who won?
Answer: The Great Emu War was a military operation undertaken in Western Australia in 1932. The Australian public, in particular farmers, were concerned about the large number of emus running amok and destroying crops. The emu is a large, flightless bird which is native to Australia. The Australian military was deployed to get the birds' numbers under control. Due to the speed of the emus and difficult terrain, the military was unsuccessful in controlling the emu numbers. It could be argued that the emus won the Great Emu War of 1932.
Question: How is digital switching possible?
Evidence: Electronics deals with electrical circuits that involve active electrical components such as vacuum tubes, transistors, diodes, sensors and integrated circuits, and associated passive interconnection technologies. The nonlinear behaviour of active components and their ability to control electron flows makes digital switching possible, and electronics is widely used in information processing, telecommunications, and signal processing. Interconnection technologies such as circuit boards, electronics packaging technology, and other varied forms of communication infrastructure complete circuit functionality and transform the mixed components into a regular working system.
Today, most electronic devices use semiconductor components to perform electron control. The underlying principles that explain how semiconductors work are studied in solid state physics, whereas the design and construction of electronic circuits to solve practical problems are part of electronics engineering.
Answer: The nonlinear behaviour of active components and their ability to control electron flows makes digital switching possible.
Question: Which state is named in the passage?
Evidence: The Brownstown Marl is a geologic formation in Arkansas. It preserves fossils dating back to the Cretaceous period.
Answer: Arkansas
Question: What are the two different continental tournaments that Roger Lemerre won ?
Evidence: In September 2002, the Tunisian Football Federation announced that it was finalizing a contract with former France manager Roger Lemerre. Tunisia hosted the 2004 African Cup of Nations, winning the group. They defeated Senegal in the quarter-finals, and Nigeria in the semi-finals. Tunisia built a 1–0 lead after four minutes with Mehdi Nafti's concentration pushed by Francileudo Santos, before Morocco levelled. Tunisia restored their lead, giving them their first African Cup of Nations title. They also won the CAF's African National Team of the Year award. Lemerre became the first manager to win two different continental tournaments, having previously won Euro 2000 with France.

As a result, Tunisia qualified for the 2005 FIFA Confederations Cup in Germany, playing the hosts, Argentina and Australia. The only points they would win was a victory over Australia. Before their 2006 World Cup appearance, Lemerre took the Tunisians to a training camp in Switzerland, where they played international friendlies against Swiss clubs. Tunisia would only record one draw in Germany, against Saudi Arabia, losing against Spain and Ukraine
Answer: Roger Lemerre won the Euro 2000 with France and the African Cup of Nations 2004 with Tunisia
Question: Why Kolkata is famous
Answer: Because of it's famous food and culture
1. Kolkata biriyani
2, Victoria
3. Rasogolla
Question: What is the game of cricket?
Evidence: Cricket is a bat-and-ball game played between two teams of eleven players on a field at the centre of which is a 22-yard (20-metre) pitch with a wicket at each end, each comprising two bails balanced on three stumps. The batting side scores runs by striking the ball bowled at one of the wickets with the bat and then running between the wickets, while the bowling and fielding side tries to prevent this (by preventing the ball from leaving the field, and getting the ball to either wicket) and dismiss each batter (so they are "out"). Means of dismissal include being bowled, when the ball hits the stumps and dislodges the bails, and by the fielding side either catching the ball after it is hit by the bat, but before it hits the ground, or hitting a wicket with the ball before a batter can cross the crease in front of the wicket. When ten batters have been dismissed, the innings ends and the teams swap roles. The game is adjudicated by two umpires, aided by a third umpire and match referee in international matches. They communicate with two off-field scorers who record the match's statistical information.
Answer: Cricket is a bat-and-ball game played between two teams. A bowler from the bowling side delivers a ball between two wickets. Two batsman are on the wicket and one of them faces the ball. They score run by hitting the ball away and running between the wicket before the ball is returned to the wicket by a fielder.
Question: Are you going for a walk today?
Answer: This is definitely the day I want to go for a walk, the weather has been rainy for so long that I haven't been able to go out. With this beautiful day, it would be a shame to stay inside!
Question: Classify each of the following as either a quantitative major or qualitative major: English, mathematics, physics, statistics, history, law
Answer: Qualitative: English, history, law 
Quantitative: mathematics, physics, statistics
Question: What are some fun ways that you could spend time with your family?
Answer: There are many different fun activities that you could do with your family. Some examples include going for a walk, visiting a museum, watching a movie, doing an arts and crafts project, playing a board game, or trying a new restaurant. Please note that your decision ought to consider factors such as the ages, health, interests, and available time of the family members.
Question: How many question-answer pairs are in the training and testing sets respectively?
Evidence: We utilize fasttext BIBREF18 to generate the embeddings of all words from both Text-SQuAD and Spoken-SQuAD. We adopt the phoneme sequence embeddings to replace the original character sequence embeddings using the method proposed by Li et al. BIBREF5 . The source domain model and the target domain model share the same set of word embedding matrix to improve the alignment between these two domains.
W-GAN is adopted for our domain discriminator BIBREF19 , which stacks 5 residual blocks of 1D convolutional layers with 96 filters and filter size 5 followed by one linear layer to convert each input vector sequence into one scalar value.
All models used in the experiments are trained with batch size 20, using adam with learning rate INLINEFORM0 and the early stop strategy. The dimension of the hidden state is set to 96 for all layers, and the number of self-attention heads is set to 2. The setup is slightly different but better than the setting suggested by the original QAnet.
There are 37,111 and 5,351 question answer pairs in the training and testing sets respectively, and the word error rate (WER) of both sets is around 22.7%.
Answer: 37,111 and 5,351 respectively.
Question: What's the most important thing in a marriage?
Answer: There're many important things in a marriage and it's hard to say what is the most important. For example, expectation management is very important. Most disappointments or arguments in a marriage come from when your partner fails to meet our expectations. It's important to communicate your expectations of each other regularly. It's also important to remember that what work for other couples or whatever the social norms are may not apply for you, and that is ok.
Question: Which of the following are chocolates: 5 Star, Dairy Milk, Bar One, Chips Ahoy, Oreo, Bounty, Mars, Milky Way, Lay's, Bananas.
Answer: 5 Star, Dairy Milk, Bar One, Bounty, Mars, Milky Way are chocolates.
Question: How about the correlation between existing automatic metrics and human judgments when the evaluation sets contain divergent references?
Evidence: The task of generating natural language descriptions of structured data (such as tables) BIBREF2 , BIBREF3 , BIBREF4 has seen a growth in interest with the rise of sequence to sequence models that provide an easy way of encoding tables and generating text from them BIBREF0 , BIBREF1 , BIBREF5 , BIBREF6 .
For text generation tasks, the only gold standard metric is to show the output to humans for judging its quality, but this is too expensive to apply repeatedly anytime small modifications are made to a system. Hence, automatic metrics that compare the generated text to one or more reference texts are routinely used to compare models BIBREF7 . For table-to-text generation, automatic evaluation has largely relied on BLEU BIBREF8 and ROUGE BIBREF9 . The underlying assumption behind these metrics is that the reference text is gold-standard, i.e., it is the ideal target text that a system should generate. In practice, however, when datasets are collected automatically and heuristically, the reference texts are often not ideal. Figure FIGREF2 shows an example from the WikiBio dataset BIBREF0 . Here the reference contains extra information which no system can be expected to produce given only the associated table. We call such reference texts divergent from the table.
We show that existing automatic metrics, including BLEU, correlate poorly with human judgments when the evaluation sets contain divergent references (§ SECREF36 ). For many table-to-text generation tasks, the tables themselves are in a pseudo-natural language format (e.g., WikiBio, WebNLG BIBREF6 , and E2E-NLG BIBREF10 ). In such cases we propose to compare the generated text to the underlying table as well to improve evaluation. We develop a new metric, PARENT (Precision And Recall of Entailed N-grams from the Table) (§ SECREF3 ). When computing precision, PARENT effectively uses a union of the reference and the table, to reward correct information missing from the reference. When computing recall, it uses an intersection of the reference and the table, to ignore extra incorrect information in the reference. The union and intersection are computed with the help of an entailment model to decide if a text n-gram is entailed by the table. We show that this method is more effective than using the table as an additional reference. Our main contributions are:
We show that existing automatic metrics, including BLEU, correlate poorly with human judgments when the evaluation sets contain divergent references (§5.4).
Answer: Poor.