DataHammer/scimrc huggingface dataset:
Question: Write a plan for a road trip to ski resorts in California that are available on the Ikon pass, with stops at three different resorts. The plan should depart and end at San Francisco, include a budget, timeline, and short description of each resort.
Answer: On day 1, start from San Francisco and drive to Palisades Tahoe, which is a roughly 200mi drive which will take around 3 hours. Palisades Tahoe, which once hosted the 1960 winter Olympics, offers two expansive mountains with a variety of beginner to advanced terrain. Finish off day 1 by driving 176mi or around 4 hours to a hotel nearby the next resort, Mammoth Mountain.

On day 2, spend the day skiing at Mammoth Mountain, which boasts high snowfalls, is home to the highest elevation lift in California, and has some of the greatest views of the Sierra Nevada mountains. Finish off day 2 by driving 314mi or around 5.5 hours to a hotel nearby the last resort, Big Bear Mountain.

On day 3, you will ski Big Bear Mountain Resort comprised of Bear Mountain, with its park-heavy terrain, and Snow Summit, with its many beginner-friendly trails. Big Bear Mountain Resort is not far from Los Angeles and San Bernardino, so additional days could be spent exploring those metro areas. Spend the night around Big Bear Mountain Resort.

On the last day, make the nearly 500mi or 7-8 hour drive back to San Francisco. Across this 4 day trip, you can expect to spend around $800 on gas costs and around $600-$800 on lodging with 1 night around Mammoth Mountain and 2 nights around Big Bear Mountain Resort.
Question: Why is the forum in Rome named the forum?
Evidence: The Roman Forum, also known by its Latin name Forum Romanum (Italian: Foro Romano), is a rectangular forum (plaza) surrounded by the ruins of several important ancient government buildings at the center of the city of Rome. Citizens of the ancient city referred to this space, originally a marketplace, as the Forum Magnum, or simply the Forum.

For centuries the Forum was the center of day-to-day life in Rome: the site of triumphal processions and elections; the venue for public speeches, criminal trials, and gladiatorial matches; and the nucleus of commercial affairs. Here statues and monuments commemorated the city's great men. The teeming heart of ancient Rome, it has been called the most celebrated meeting place in the world, and in all history. Located in the small valley between the Palatine and Capitoline Hills, the Forum today is a sprawling ruin of architectural fragments and intermittent archaeological excavations attracting 4.5 million or more sightseers yearly.
Answer: The Forum in Rome is the location of the ruins of the ancient city of Rome.  The forum is derived from Latin, meaning rectangular plaza.  The plaza was the center of activity in Rome.  Staging speeches trials and public gatherings.
Question: Are the authors the first to study early natural language cues through a data-driven?
Evidence: Negotiations, either between individuals or entities, are ubiquitous in everyday human interactions ranging from sales to legal proceedings. Being a good negotiator is a complex skill, requiring the ability to understand the partner's motives, ability to reason and to communicate effectively, making it a challenging task for an automated system. While research in building automatically negotiating agents has primarily focused on agent-agent negotiations BIBREF0, BIBREF1, there is a recent interest in agent-human negotiations BIBREF2 as well. Such agents may act as mediators or can be helpful for pedagogical purposes BIBREF3.
Efforts in agent-human negotiations involving free-form natural language as a means of communication are rather sparse. Researchers BIBREF4 recently studied natural language negotiations in buyer-seller bargaining setup, which is comparatively less restricted than previously studied game environments BIBREF5, BIBREF6. Lack of a well-defined structure in such negotiations allows humans or agents to express themselves more freely, which better emulates a realistic scenario. Interestingly, this also provides an exciting research opportunity: how can an agent leverage the behavioral cues in natural language to direct its negotiation strategies? Understanding the impact of natural language on negotiation outcomes through a data-driven neural framework is the primary objective of this work.
We focus on buyer-seller negotiations BIBREF4 where two individuals negotiate the price of a given product. Leveraging the recent advancements BIBREF7, BIBREF8 in pre-trained language encoders, we attempt to predict negotiation outcomes early on in the conversation, in a completely data-driven manner (Figure FIGREF3). Early prediction of outcomes is essential for effective planning of an automatically negotiating agent. Although there have been attempts to gain insights into negotiations BIBREF9, BIBREF10, to the best of our knowledge, we are the first to study early natural language cues through a data-driven neural system (Section SECREF3). Our evaluations show that natural language allows the models to make better predictions by looking at only a fraction of the negotiation. Rather than just realizing the strategy in natural language, our empirical results suggest that language can be crucial in the planning as well. We provide a sample negotiation from the test set BIBREF4 along with our model predictions in Table TABREF1.
Although there have been attempts to gain insights into negotiations, to the best of our knowledge, we are the first to study early natural language cues through a data-driven neural system (Section  2).
Answer: Yes, they are.
Question: What is one of Poseidon's many powers?
Evidence: The Call to Adventure
The hero begins in a situation of normality from which some information is received that acts as a call to head off into the unknown. According to Campbell, this region is represented by

a distant land, a forest, a kingdom underground, beneath the waves, or above the sky, a secret island, lofty mountaintop, or profound dream state; but it is always a place of strangely fluid and polymorphous beings, unimaginable torments, superhuman deeds, and impossible delight. The hero can go forth of their own volition to accomplish the adventure, as did Theseus when he arrived in his father's city, Athens, and heard the horrible history of the Minotaur; or they may be carried or sent abroad by some benign or malignant agent as was Odysseus, driven about the Mediterranean by the winds of the angered god, Poseidon. The adventure may begin as a mere blunder... or still, again, one may be only casually strolling when some passing phenomenon catches the wandering eye and lures one away from the frequented paths of man. Examples might be multiplied, ad infinitum, from every corner of the world.
Answer: Poseidon has power to control the winds that guide ships on the seas of the Mediterranean.
Question: Where to visit in Brazil?
Answer: It depends what you are looking for. Brazil is known for the amazon forest, carnival and beaches in Rio but there are a lot more to explore.

There are pretty interesting cities, such as São Paulo, Curitiba and Recife. São Paulo has a great mix of culture and gastronomy, the city is vibrant and have bakeries that stay up all night. Curitiba became a leader in urban sustainability and also has a cultural aspect to it.
Recife is a city in the northeastern state of Pernambuco, it has a night life in its old town, Recife antigo and some beaches as well. During the month of February the city has a vibrant carnival celebration, tourists and residents go out to the street to dance and celebrate, where you can see people of all ages.

Besides the cities, Brazil has beautiful warm beaches in its northeastern states. From the Bahia state to Ceára state, there are many paradisiac beaches to visit. Be aware that road tripping in Brazil is not always safe and you need to speak Portuguese since you will find English speakers only in the main hotels and resorts. Stay in the main cities of Salvador, Aracajú, Maceió, Recife, João Pessoa, Natal and Fortaleza to experience the most development and tourist services.
Question: What is a term deposit?
Answer: With a term deposit, you lock away an amount of money for an agreed length of time (the 'term') – that means you can't access the money until the term is up. In return, you'll get a guaranteed rate of interest for the term you select, so you'll know exactly what the return on your money will be.
Question: Why kids who pursue athletics do well in professional life ?
Answer: Study shows that kids who pursue athletics are on average more successful in their professional life.  This can largely attributed to traits  such as grit, practice, competitiveness, teamwork, passion and drive that athletics fosters in participating kids.  These traits continue to serve well as individuals grow into their professional life.
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Question: What is the biggest threat to the great barrier reef?
Evidence: The Great Barrier Reef Marine Park Authority considers the greatest threat to the Great Barrier Reef to be climate change, causing ocean warming which increases coral bleaching. Mass coral bleaching events due to marine heatwaves occurred in the summers of 1998, 2002, 2006, 2016, 2017 and 2020, and coral bleaching is expected to become an annual occurrence. In 2020, a study found that the Great Barrier Reef has lost more than half of its corals since 1995 due to warmer seas driven by climate change. As global warming continues, corals will not be able to keep up with increasing ocean temperatures. Coral bleaching events lead to increased disease susceptibility, which causes detrimental ecological effects for reef communities.
Answer: Climate change is the biggest threat to the Great Barrier Reef. Major heat waves over the past 30 years have increased coral bleaching and is now expected to occur yearly. Coral bleaching increases the likelihood of disease and is therefore destroying reef communities.
Question: How do the n-gram features incorporate compositionality?
Evidence: We propose a new unsupervised model, Sent2Vec, for learning universal sentence embeddings. Conceptually, the model can be interpreted as a natural extension of the word-contexts from C-BOW BIBREF0 , BIBREF1 to a larger sentence context, with the sentence words being specifically optimized towards additive combination over the sentence, by means of the unsupervised objective function.
Formally, we learn a source (or context) embedding INLINEFORM0 and target embedding INLINEFORM1 for each word INLINEFORM2 in the vocabulary, with embedding dimension INLINEFORM3 and INLINEFORM4 as in ( EQREF6 ). The sentence embedding is defined as the average of the source word embeddings of its constituent words, as in ( EQREF8 ). We augment this model furthermore by also learning source embeddings for not only unigrams but also n-grams present in each sentence, and averaging the n-gram embeddings along with the words, i.e., the sentence embedding INLINEFORM5 for INLINEFORM6 is modeled as DISPLAYFORM0
We propose a new unsupervised model, Sent2Vec, for learning universal sentence embeddings
Formally, we learn a source (or context) embedding INLINEFORM0 and target embedding INLINEFORM1 for each word INLINEFORM2 in the vocabulary, with embedding dimension INLINEFORM3 and INLINEFORM4 as in ( EQREF6 ). The sentence embedding is defined as the average of the source word embeddings of its constituent words, as in ( EQREF8 ). We augment this model furthermore by also learning source embeddings for not only unigrams but also n-grams present in each sentence, and averaging the n-gram embeddings along with the words, i.e., the sentence embedding INLINEFORM5 for INLINEFORM6 is modeled as DISPLAYFORM0
Answer: The answers are shown as follows:
* by also learning source embeddings for not only unigrams but also n-grams present in each sentence, and averaging the n-gram embeddings along with the words
Question: Is the dataset multilingual?
Evidence: We use a new dataset of GD statements from 1970 to 2016, the UN General Debate Corpus (UNGDC), to examine the international development agenda in the UN BIBREF3 . Our application of NLP to these statements focuses in particular on structural topic models (STMs) BIBREF4 . The paper makes two contributions using this approach: (1) It sheds light on the main international development issues that governments prioritise in the UN; and (2) It identifies the key country-specific factors associated with governments discussing development issues in their GD statements.
FLOAT SELECTED: Fig. 2. Topic quality. 20 highest probability words for the 16-topic model.
We use a new dataset of GD statements from 1970 to 2016, the UN General Debate Corpus (UNGDC), to examine the international development agenda in the UN BIBREF3 . 
FLOAT SELECTED: Fig. 2. Topic quality. 20 highest probability words for the 16-topic model.
Answer: No.
Question: Which dimensionality do they use for their embeddings?
Evidence: Our classifier-based embeddings use LSTM or GRU networks with 2–4 stacked layers and 1–3 fully connected layers. The final embedding dimensionality is equal to the number of unique word labels in the training set, which is 1061. The recurrent hidden state dimensionality is fixed at 512 and dropout BIBREF32 between stacked recurrent layers is used with probability INLINEFORM0 . The fully connected hidden layer dimensionality is fixed at 1024. Rectified linear unit (ReLU) non-linearities and dropout with INLINEFORM1 are used between fully-connected layers. However, between the final recurrent hidden state output and the first fully-connected layer no non-linearity or dropout is applied. These settings were determined through experiments on the development set.
The final embedding dimensionality is equal to the number of unique word labels in the training set, which is 1061.
Answer: The answers are shown as follows:
* 1061
Question: What kind of method is Transfer printing
Answer: Transfer printing is a method of decorating pottery or other materials using an engraved copper or steel plate from which a monochrome print on paper is taken which is then transferred by pressing onto the ceramic piece. Pottery decorated using the technique is known as transferware or transfer ware.

It was developed in England from the 1750s on, and in the 19th century became enormously popular in England, though relatively little used in other major pottery-producing countries. The bulk of production was from the dominant Staffordshire pottery industry. America was a major market for English transfer-printed wares, whose imagery was adapted to the American market; several makers made this almost exclusively.

The technique was essential for adding complex decoration such as the Willow pattern to relatively cheap pottery. In particular, transfer printing brought the price of a matching dinner service low enough for large numbers of people to afford.

Apart from pottery, the technique was used on metal, and enamelled metal, and sometimes on wood and textiles. It remains used today, although mostly superseded by lithography. In the 19th century methods of transfer printing in colour were developed.
Question: Explain me the concept of "Karma" in Buddhism.
Answer: Karma is one of the most misunderstood aspects of Buddhism. In simple terms, Karma is the law of action and reactions. Our actions, both physical and thoughts, are the acts that are put in the world. Reactions can be referred to as their manifestations in the actor's life, i.e. our own life. For example, suppose your mind is filled with greed, evil thoughts like harming another person, and jealousy. In that case, it reflects restlessness as we will never be satisfied, punishments for harming another person, and stress to become like someone else, respectively. For a positive example, a life lived with generosity, righteousness, kindness, and genuinely putting good out there will lead to respect in society and a fulfilled life. Furthermore, Buddhism believes in reincarnation. So the good acts and deeds that one puts in this life, one also reaps the benefits in the next life. Therefore, the equation of Karma is relatively straightforward. Do good and work for the betterment of society and oneself.
Question: Classify the following games in ascending order of computational complexity: tic-tac-toe, chess, checkers, go
Answer: tic-tac-toe, checkers, chess, go
Question: Why is standard guitar tuning EADGBE?
Answer: The standard guitar tuning of EADGBE offers consistency and convenience. The interval between each successive pair of strings is a perfect fourth, except the major third interval between G and B, making some figures and phrases 'translate' horizontally across the neck. The perfect fourth interval helps avoid long finger stretches in comparison to the perfect fifth intervals on smaller instruments like the violin. The introduction of a major third between G and B means that the total interval between 1st and 6th string is 24 semitones, or 2 octaves, making the open guitar strings fall more easily into chords, aiding fretting of basic chords with fewer fingers.
Question: How many short texts are analyzed in the study?
Evidence: The database consists of 1,000 short texts, each having 10-40 words. Out of these, 350 are sarcastic and are collected as follows: (a) 103 sentences are from two popular sarcastic quote websites, (b) 76 sarcastic short movie reviews are manually extracted from the Amazon Movie Corpus BIBREF11 by two linguists. (c) 171 tweets are downloaded using the hashtag #sarcasm from Twitter. The 650 non-sarcastic texts are either downloaded from Twitter or extracted from the Amazon Movie Review corpus. The sentences do not contain words/phrases that are highly topic or culture specific. The tweets were normalized to make them linguistically well formed to avoid difficulty in interpreting social media lingo. Every sentence in our dataset carries positive or negative opinion about specific “aspects”. For example, the sentence “The movie is extremely well cast” has positive sentiment about the aspect “cast”.


The annotators were seven graduate students with science and engineering background, and possess good English proficiency. They were given a set of instructions beforehand and are advised to seek clarifications before they proceed. The instructions mention the nature of the task, annotation input method, and necessity of head movement minimization during the experiment.
The database consists of 1,000 short texts, each having 10-40 words.
Answer: 1000 short texts.
Question: When did Alaska become a state?
Answer: Alaska became a state on January 3, 1959.
Question: Where was the heaviest A single filmed?
Evidence: "Nothing" is the first single by English rock band A released from their album Hi-Fi Serious. It reached number nine in the UK Singles Chart; to date, A's highest charting single. During the promotion of the single, the band appeared on Top of The Pops and the Pepsi Chart Show.

The promotional video for Nothing was filmed in Cape Town, South Africa, mostly around the Artscape Theatre Centre formerly known as the Nico Malan theatre complex, and features extras dressed in the same clothes as each band member - complete with band member masks - to create the illusion that there are hundreds of duplicates of the band.

"Nothing" is arguably the heaviest A single, marking something of a departure from the band's usual melodic pop punk to nu metal. It is track 1 on the album Hi-Fi Serious. A live version appears on the live album, Rockin' Like Dokken.
Answer: A's first hit single Nothing was filmed in Cape Town, South Africa.
Question: Given this reference test, what is the daily recommended value of magnesium for men in the U.S.?
Evidence: In the UK, the recommended daily values for magnesium are 300 mg for men and 270 mg for women. In the U.S. the Recommended Dietary Allowances (RDAs) are 400 mg for men ages 19–30 and 420 mg for older; for women 310 mg for ages 19–30 and 320 mg for older.
Answer: The daily recommended value of magnesium for men in the U.S. is 400 mg.
Question: What are the different ways I can open a jar whose lid is stuck and will not open?
Answer: 1. Using a rubber band or rubber glove - Surround the circumference of the lid with a rubber band and now try to open the lid the same way you would normally do. The rubber band creates additional friction which causes helps open the lid with less force. The same result can be achieved by using rubber glove. 
2. Using hot water - Hold the jar under hot water, the hot water will allow the metal lid to expand allowing you to open the jar. 
3. Using a knife - Break the vacuum seal by poking a hole in the lid using a sharp object such as a knife. Once the vacuum seal is broken, you can twist open the lid with less force.
Question: In the example of Figure 1, why do the team consider the reference text divergent from the associated table?
Evidence: We briefly review the task of generating natural language descriptions of semi-structured data, which we refer to as tables henceforth BIBREF11 , BIBREF12 . Tables can be expressed as set of records INLINEFORM0 , where each record is a tuple (entity, attribute, value). When all the records are about the same entity, we can truncate the records to (attribute, value) pairs. For example, for the table in Figure FIGREF2 , the records are {(Birth Name, Michael Dahlquist), (Born, December 22 1965), ...}. The task is to generate a text INLINEFORM1 which summarizes the records in a fluent and grammatical manner. For training and evaluation we further assume that we have a reference description INLINEFORM2 available for each table. We let INLINEFORM3 denote an evaluation set of tables, references and texts generated from a model INLINEFORM4 , and INLINEFORM5 , INLINEFORM6 denote the collection of n-grams of order INLINEFORM7 in INLINEFORM8 and INLINEFORM9 , respectively. We use INLINEFORM10 to denote the count of n-gram INLINEFORM11 in INLINEFORM12 , and INLINEFORM13 to denote the minimum of its counts in INLINEFORM14 and INLINEFORM15 . Our goal is to assign a score to the model, which correlates highly with human judgments of the quality of that model.
In Figure 1, the reference, though technically correct and fluent, mentions information which cannot be gleaned from the associated table. It also fails to mention useful information which a generation system might correctly include (e.g. candidate 3 in the figure). We call such references divergent from the associated table.
Answer: Because it mentions information which cannot be gleaned from the associated table. It also fails to mention useful information which a generation system might correctly include.
Question: Which dataset do they use a starting point in generating fake reviews?
Evidence: We use the Yelp Challenge dataset BIBREF2 for our fake review generation. The dataset (Aug 2017) contains 2.9 million 1 –5 star restaurant reviews. We treat all reviews as genuine human-written reviews for the purpose of this work, since wide-scale deployment of machine-generated review attacks are not yet reported (Sep 2017) BIBREF19 . As preprocessing, we remove non-printable (non-ASCII) characters and excessive white-space. We separate punctuation from words. We reserve 15,000 reviews for validation and 3,000 for testing, and the rest we use for training. NMT models require a parallel corpus of source and target sentences, i.e. a large set of (source, target)-pairs. We set up a parallel corpus by constructing (context, review)-pairs from the dataset. Next, we describe how we created our input context.
We use the Yelp Challenge dataset BIBREF2 for our fake review generation. 
Answer: The answers are shown as follows:
* the Yelp Challenge dataset