DataHammer/scimrc huggingface dataset:
Question: Write a short story about Batman, Superman and Spiderman
Answer: Batman, Superman and Spiderman were all out patrolling the streets when they came across a mysterious figure in a long black cape and a mask. They quickly realized it was none other than The Joker. The Joker had been planning a grand scheme to take over the city and they needed to stop him before it was too late. 

Batman quickly devised a plan. He would disguise himself as a clown, while Superman would disguise himself as a giant robot and Spiderman would disguise himself as a spider. The Joker was fooled and was easily captured. The city was saved and the Joker was taken away to prison.
Question: What is the baseline approach in the article?
Evidence: In the literature, the main consensus is that the use of dense word embeddings outperform the sparse embeddings in many tasks. Latent semantic analysis (LSA) used to be the most popular method in generating word embeddings before the invention of the word2vec and other word vector algorithms which are mostly created by shallow neural network models. Although many studies have been employed on generating word vectors including both semantic and sentimental components, generating and analysing the effects of different types of embeddings on different tasks is an emerging field for Turkish.
Latent Dirichlet allocation (LDA) is used in BIBREF2 to extract mixture of latent topics. However, it focusses on finding the latent topics of a document, not the word meanings themselves. In BIBREF3, LSA is utilised to generate word vectors, leveraging indirect co-occurrence statistics. These outperform the use of sparse vectors BIBREF4.
Some of the prior studies have also taken into account the sentimental characteristics of a word when creating word vectors BIBREF5, BIBREF6, BIBREF7. A model with semantic and sentiment components is built in BIBREF8, making use of star-ratings of reviews. In BIBREF9, a sentiment lexicon is induced preferring the use of domain-specific co-occurrence statistics over the word2vec method and they outperform the latter.
In a recent work on sentiment analysis in Turkish BIBREF10, they learn embeddings using Turkish social media. They use the word2vec algorithm, create several unsupervised hand-crafted features, generate document vectors and feed them as input into the support vector machines (SVM) approach. We outperform this baseline approach using more effective word embeddings and supervised hand-crafted features.
In English, much of the recent work on learning sentiment-specific embeddings relies only on distant supervision. In BIBREF11, emojis are used as features and a bi-LSTM (bidirectional long short-term memory) neural network model is built to learn sentiment-aware word embeddings. In BIBREF12, a neural network that learns word embeddings is built by using contextual information about the data and supervised scores of the words. This work captures the supervised information by utilising emoticons as features. Most of our approaches do not rely on a neural network model in learning embeddings. However, they produce state-of-the-art results.
In a recent work on sentiment analysis in Turkish [11], they learn embeddings using Turkish social media. They use the word2vec algorithm, create several unsupervised hand-crafted features, generate document vectors and feed them as input into the support vector machines (SVM) approach. We outperform this baseline approach using more effective word embeddings and supervised hand-crafted features.
Answer: The word2vec algorithm.
Question: What is the largest fresh water lake?
Evidence: Lake Baikal (/baɪˈkɑːl, -ˈkæl/, Russian: Oзеро Байкал, romanized: Ozero Baykal [ˈozʲɪrə bɐjˈkaɫ]) is a rift lake in Russia. It is situated in southern Siberia, between the federal subjects of Irkutsk Oblast to the northwest and the Republic of Buryatia to the southeast. With 23,615.39 km3 (5,670 cu mi) of water, Lake Baikal is the world's largest freshwater lake by volume, containing 22–23% of the world's fresh surface water, more than all of the North American Great Lakes combined. It is also the world's deepest lake, with a maximum depth of 1,642 metres (5,387 feet; 898 fathoms), and the world's oldest lake, at 25–30 million years. At 31,722 km2 (12,248 sq mi)—slightly larger than Belgium—Lake Baikal is the world's seventh-largest lake by surface area. It is among the world's clearest lakes.

Baikal's age is estimated at 25–30 million years, making it the most ancient lake in geological history. It is unique among large, high-latitude lakes, as its sediments have not been scoured by overriding continental ice sheets. Russian, U.S., and Japanese cooperative studies of deep-drilling core sediments in the 1990s provide a detailed record of climatic variation over the past 6.7 million years.
Answer: Lake Baikal, located in Russia in the southern region of Sibera is the largest and deepest fresh water lake, containing 20% of Earth's fresh surface water.
Question: How much improvement does their method get over the fine tuning baseline?
Evidence: FLOAT SELECTED: Table 1: Domain adaptation results (BLEU-4 scores) for IWSLT-CE using NTCIR-CE.
FLOAT SELECTED: Table 1: Domain adaptation results (BLEU-4 scores) for IWSLT-CE using NTCIR-CE.
Answer: 0.08 points on the 2011 test set, 0.44 points on the 2012 test set, 0.42 points on the 2013 test set for IWSLT-CE.
Question: Give me a list of the best ways of looking younger than your age.
Answer: To keep fit, maintain clear skin, be positive, always be up-to-date to everything, do not hesitate to change, be calm
Question: When was the first newspaper published in the United States?
Answer: "Publick Occurrences Both Forreign and Domestick" was the first US newspaper published on September 25, 1690.
Question: What are magical creatures?
Answer: Magical creatures are an aspect of the fictional Wizarding World contained in the Harry Potter series and connected media originally created by British author J. K. Rowling. Throughout the seven main books of the series, Harry and his friends encounter many of these creatures on their adventures in Hogwarts, the Forbidden Forest, or other locations throughout the Wizarding World. In addition, students learn to take care of creatures such as hippogriffs and unicorns in the Care of Magical Creatures class at Hogwarts. Rowling has also written Fantastic Beasts and Where to Find Them, a guide to the magical beasts found in the series, and based on the fictional textbook of the same name written by Newt Scamander and used by students at Hogwarts.
Some creatures in the series are ordinary animals that may be imbued with magical properties or possess certain magical abilities. Owls, for example, deliver mail and have the ability to find the recipient regardless of their location. Other animals such as cats, dogs, frogs, toads, rats and mice do not necessarily have magical abilities.
Question: What were the evaluation metrics used?
Evidence: Our experimental results are shown in Table TABREF21. The first half of the table contains results for task-oriented dialogue with the Sequicity framework with two scenarios for training data preparation. For each experiment, we run our models for 3 times and their scores are averaged as the final score. The mixed training scenario performs the mixing of both the training data, development data and the test data as described in the previous subsection. The non-mixed training scenario performs the mixing only on the development and test data, keeps the training data unmixed as in the original KVRET dataset. As in the Sequicity framework, we report entity match rate, BLEU score and Success F1 score. Entity match rate evaluates task completion, it determines if a system can generate all correct constraints to search the indicated entities of the user. BLEU score evaluates the language quality of generated responses. Success F1 balances the recall and precision rates of slot answers. For further details on these metrics, please refer to BIBREF8.
As in the Sequicity framework, we report entity match rate, BLEU score and Success F1 score. 
Answer: The answers are shown as follows:
* entity match rate
* BLEU score
* Success F1 score
Question: Where was the first season of The X-Files filmed?
Answer: The first season of the X-Files was filmed in Vancouver, British Columbia, Canada.
Question: What extraction model did they use?
Evidence: FLOAT SELECTED: Figure 1: Multi-Encoder, Constrained-Decoder model for tuple extraction from (q, a).
FLOAT SELECTED: Figure 1: Multi-Encoder, Constrained-Decoder model for tuple extraction from (q, a).
Answer: Multi-Encoder, Constrained-Decoder model
Question: What are some of the main themes of Jane Eyre
Answer: Some of the main themes of Jane Eyre are social class, love, family, dependence and independence, personal discovery and growth.  There are also themes of religion, pride, duty to society and personal morality
Question: My partner is a 30 year old male who likes to travel, read books, cook, and paint. What are some good gift ideas for his upcoming birthday?
Answer: There are a lot of options to consider for your partner based on his interests. Below are a few suggestions:

1. Art class
2. A wine and paint experience
3. A couple cooking class. Ex: Gnocchi making class
4. Plan a surprise trip to his favorite destination
5. Gift him a book on his favorite topic
6. Gift him an audio book subscription

Most important part of the gift is to showcase the effort and make sure you both have a good time!
Question: Which is a species of fish? Boar or Boarfish
Answer: Boarfish
Question: What might make a good villain for a fantasy role playing game adventure.
Answer: There are lots of options for villains in the rich world of fantasy role playing.   Here are some possibilities:
1) Dragons - Dragons are iconic villains and come in many varieties.  They can be vicious and cruel, manipulative and clever, or haughty and imperious.  They live in all different biomes and there are even variants for different cultures (like western dragons vs. eastern dragons)
2) Wizards - The evil wizard is the classic fantasy villain.  Possessing great and broad reaching powers, driven by the need to obtain more magical power, and often surrounded by a horde of lesser minions, wizards fit all sorts of scenarios.
3) Undead, especially Liches and Vampires - The undead are always great villains.  Liches and Vampires are especially good as they are very intelligent and powerful.  Often, they are wizards so they combine more than one kind of villain.  They also typically have the ability to create more of their kind or lesser undead to serve as minions.
4) Devils or Demons - Monstrous beings from the lower planes possessing great power and able to twist mortals to their will, devils and demons make classic fantasy villains.  While they are typically very dangerous in battle, they also have the power to manipulate and corrupt mortals to do their bidding.

These are just some of the options you could use for fantasy villains, there are many more as the domain of fantasy adventure is nearly unlimited.
Question: What bosses are there and what is their loot in Chapter four season 2 in Fortnite
Answer: In the game “Fortnite” there are currently two NPC bosses. One in the location Mega City, the other in the Landmark, Shattered Slabs. In Mega City, the NPC boss “Highcard Havoc” has loot of the gun  Havoc Suppressed Assault Rifle, the rarity is Mythical. The NPC boss also has loot of a Vault Keycard item, which can unlock a small domain called a vault. The NPC boss also has two NPC guards that are neutral: They only attack if fired upon. The NPC guard has a 100% chance of having loot of a Rare Twin Mag SMG, and a 20 small ammo. In the Landmark Shattered Slabs. The process is the exact same, but the vault is in a different location. One vault keycard cannot open both of the vaults. This boss spawns after two minutes in the game, which is one full storm circle.
Question: What programming languages does freeCodeCamp teach to students?
Evidence: freeCodeCamp (also referred to as Free Code Camp) is a non-profit organization that consists of an interactive learning web platform, an online community forum, chat rooms, online publications and local organizations that intend to make learning web development accessible to anyone. Beginning with tutorials that introduce students to HTML, CSS and JavaScript, students progress to project assignments that they complete either alone or in pairs. Upon completion of all project tasks, students are partnered with other nonprofits to build web applications, giving the students practical development experience.
Answer: freeCodeCamp is a non-profit organization that has tutorials that introduce students to HTML, CSS and JavaScript.
Question: Given this paragraph about mushroom growth, why is it related to the English language expression "to mushroom"?
Evidence: Many species of mushrooms seemingly appear overnight, growing or expanding rapidly. This phenomenon is the source of several common expressions in the English language including "to mushroom" or "mushrooming" (expanding rapidly in size or scope) and "to pop up like a mushroom" (to appear unexpectedly and quickly). In reality, all species of mushrooms take several days to form primordial mushroom fruit bodies, though they do expand rapidly by the absorption of fluids.
Answer: This is because many types of mushrooms exhibit rapid growth, seemingly overnight due to fluid absorption.
Question: Come up with a bunch of options for a child's Birthday Party
Answer: - Celebrate at home with cake, ice cream, streamers and the child's closest friends
- Go to the local swimming pool and have a pool party!
- Enjoy a day at the local chuck-e-cheese
- Go to a video game arcade with all their friends
- Have fun at your local water slide park, if it's outdoors make sure to go during summer months
- Enjoy a day at the beach if you're on the coast
- Enjoy an afternoon at your local park, maybe reserve a picnic table!
Question: What model do the authors want to learn in the future?
Evidence: We present a multi-task learning architecture to learn NMT for search query translation. As the motivating task is CLIR, we evaluated the ranking effectiveness of our proposed architecture. We used sentences from the target side of the parallel corpus as queries to retrieve relevant document and use terms from those documents to train a word embedding model along with NMT. One big challenge in this landscape is to sample meaningful queries from sentences as sentences do not directly convey information need. In the future, we hope to learn models that are able to sample search queries or information needs from sentences and use the output of that model to get relevant documents.
In the future, we hope to learn models that are able to sample search queries or information needs from sentences and use the output of that model to get relevant documents
Answer: The models are able to sample search queries or information needs from sentences and use the output of that model to get relevant documents.
Question: According to this paragraph, did Frederic Foley hold the patent to the Foley catheter?
Evidence: Foley first described the use of a self-retaining balloon catheter in 1929, to be used to achieve hemostasis after cystoscopic prostatectomy. He worked on development of this design for use as an indwelling urinary catheter, to provide continuous drainage of the bladder, in the 1930s. His design incorporated an inflatable balloon towards the tip of the tube which could be inflated inside the bladder to retain the catheter without external taping or strapping. He demonstrated this to the American Urologists Society in 1935, and published a paper describing it in 1937. While he was still developing his catheter, a patent was issued to Paul Raiche of the Davol Rubber Company of Providence, Rhode Island in 1936. Four months later, in October 1936, Foley applied for the patent, and was awarded this after appearing before the patent office Board of Appeals. Raiche appealed this decision in court, and it was overturned, returning the patent to Raiche. A further request for a hearing made by Foley was refused, and so the patent stayed with Raiche.
https://en.wikipedia.org/wiki/Frederic_Foley
Answer: According to this paragraph, Frederic Foley applied for the patent but it was ultimately awarded to Paul Riache instead.
Question: is keto diet healthy?
Answer: The keto diet is originally designed in clinics to relieve seizure symptoms in children with epilepsy. The diet prescribes intake of nutrients be majority from fat, a small percentage from protein, and very low carbohydrate. The low carbohydrates diet is adopted by people who want to lose weight. Some claim that they burn fat more effectively and reduce glucose levels because the diet makes you feel less hungry after each meal and limits the amount of sugar. However, solid research proof of the diet’s effectiveness in treating obesity or diabetes is limited. As a highly imbalanced nutrient diet, keeping a long-term keto diet can be challenging or even risky. Long-term keto diet could cause low blood pressure, kidney stones, constipation, nutrient deficiencies, eating disorder, and an increased risk of heart disease. Strict diets like keto could also cause social isolation or disordered eating. Keto should be taken with extra caution for people with pre-existing medical conditions like high blood pressure or heart diseases.
Question: King Charles III is 73 years old and his full name is?
Answer: Charles Philip Arthur George
Question: Who recieves a dowry?
Evidence: A dowry is a payment, such as property or money, paid by the bride's family to the groom or his family at the time of marriage. Dowry contrasts with the related concepts of bride price and dower. While bride price or bride service is a payment by the groom, or his family, to the bride, or her family, dowry is the wealth transferred from the bride, or her family, to the groom, or his family. Similarly, dower is the property settled on the bride herself, by the groom at the time of marriage, and which remains under her ownership and control.
Answer: A dowry is a payment from a bride's family to the groom or his family at the time of marriage.
Question: What is a top spin serve in tennis?
Answer: In tennis, a topspin serve is a type of serve that involves brushing the tennis racket upwards against the ball such that the top of the ball spins forward. This causes the ball to dive down faster than a flat serve. It also causes the ball to bounce higher than a flat serve. Because the server isn't hitting the ball flat and some of their energy is spent adding spin, it is often slower than a hard flat serve.
Question: What are the best types of pets for a family with kids?
Answer: The best types of pets for a family to get are those that match the energy level and time commitment that the family is willing to commit to. For example, if the family is frequently going to be away on trips, they should think about if their absence would cause stress for the pet and how much care they would need to arrange for the pet while they are away. Types of pets that involve less time and care are: Fish, snakes and turtles. Pets that involve more time and care are: Dogs, Cats, Birds, Guinea pigs, and hamsters.
Question: What does the author analyze from the data in Table 7?
Evidence: We performed an error analysis on 50 ARC questions where the BERT-QC system did not predict the correct label, with a summary of major error categories listed in Table TABREF20 .
Associative Errors: In 35% of cases, predicted labels were nearly correct, differing from the correct label only by the finest-grained (leaf) element of the hierarchical label (for example, predicting Matter INLINEFORM0 Changes of State INLINEFORM1 Boiling instead of Matter INLINEFORM2 Changes of State INLINEFORM3 Freezing). The bulk of the remaining errors were due to questions containing highly correlated words with a different class, or classes themselves being highly correlated. For example, a specific question about Weather Models discusses “environments” changing over “millions of years”, where discussions of environments and long time periods tend to be associated with questions about Locations of Fossils. Similarly, a question containing the word “evaporation” could be primarily focused on either Changes of State or the Water Cycle (cloud generation), and must rely on knowledge from the entire question text to determine the correct problem domain. We believe these associative errors are addressable technical challenges that could ultimately lead to increased performance in subsequent models.
Errors specific to the multiple-choice domain: We observed that using both question and all multiple choice answer text produced large gains in question classification performance – for example, BERT-QC performance increases from 0.516 (question only) to 0.654 (question and all four answer candidates), an increase of 0.138 MAP. Our error analysis observed that while this substantially increases QC performance, it changes the distribution of errors made by the system. Specifically, 25% of errors become highly correlated with an incorrect answer candidate, which (we show in Section SECREF5 ) can reduce the performance of QA solvers.
Table 7: BERT-QC Error Analysis: Classes of errors for 50 randomly selected questions from the development set where BERT-QC did not predict the correct label. These errors reflect the BERT-QC model trained and evaluated with terms from both the question and all multiple choice answer candidates. Questions can occupy more than one error category, and as such proportions do not sum to 100%.
Answer: BERT-QC Error Analysis: Classes of errors for 50 randomly selected questions from the development set where BERT-QC did not predict the correct label. These errors reflect the BERT-QC model trained and evaluated with terms from both the question and all multiple choice answer candidates. Questions can occupy more than one error category, and as such proportions do not sum to 100%.
Question: Who was On the Point of Death directed by, given the following information?
Evidence: Fabio Garriba (13 November 1944 – 9 August 2016) was an Italian stage, film and television actor.

Life and career
Born in Soave, Garriba started his career on stage, and in 1969 he made his film debut in Dziga Vertov Group's Wind from the East. He later worked with prominent directors such as Roberto Rossellini, Bernardo Bertolucci, Ettore Scola, Marco Bellocchio and Luigi Magni. He also had leading roles in films directed by his twin brother Mario, notably the Golden Leopard winner On the Point of Death.

Garriba also worked as assistant director for Bernardo Bertolucci, Pier Paolo Pasolini, Marco Ferreri and Carmelo Bene. His only work as director, the short film I parenti tutti, was screened at the 68th Venice International Film Festival alongside his brother's works in the retrospective "Orizzonti 1960-1978". Garriba also published several collections of poetries.
Answer: Mario Garriba directed On the Point of Death which stars his brother Fabio in a leading role.
Question: Classify the below numbers based on whether they are perfect square or not.
64, 9, 81, 100, 57, 16
Answer: Perfect square - 64, 9, 81, 16
Not perfect square - 100, 57
Question: What helped Argentina win the World Cup, considering they were not the strongest team on paper?
Answer: Argentina in its run to the World Cup had a great track record of a continuous winning streak. It was complemented by the culture and passion for football infused in the country. The team played with a lot of passion and Lionel Messi was determined to create history.
Question: What are the best Classic Rock bands?
Answer: While subjective, most Classic Rocks fans would all agree that Led Zeppelin, The Who, Pink Floyd, Cream, The Doors, Queen, The Rolling Stones, Yes, Jimi Hendrix, Jefferson Airplane, The Moody Blues and Allman Brothers would all make the list.  There are many others like the Beatles and Grateful Dead etc that might be considered Classic Rock but also fall in other genres.
Question: Are dogs carnivores or omnivores?
Answer: Well, they're omnivores since dogs eat both plant based and animal based food.