DataHammer/scimrc huggingface dataset:
Question: Are the resource presented by the authors useful for building language systems in an endangered, under-represented language, Mapudungun?
Evidence: With this work we present a resource that will be extremely useful for building language systems in an endangered, under-represented language, Mapudungun. We benchmark NLP systems for speech synthesis, speech recognition, and machine translation, providing strong baseline results. The size of our resource (142 hours, more than 260k total sentences) has the potential to alleviate many of the issues faced when building language technologies for Mapudungun, in contrast to other indigenous languages of the Americas that unfortunately remain low-resource.
Our resource could also be used for ethnographic and anthropological research into the Mapuche culture, and has the potential to contribute to intercultural bilingual education, preservation activities and further general advancement of the Mapudungun-speaking community.
With this work we present a resource that will be extremely useful for building language systems in an endangered, under-represented language, Mapudungun.
Answer: Yes, it is.
Question: Why are In-N-Out cheeseburgers so good?
Answer: In-N-Out cheeseburgers are seen as good for a few reasons.  The meat is never frozen and tight quality controls at their processing plants insure a consistent and high quality meat patty.  The incentive structure for the In-n-out employee results in workers staying at the fast food chain longer with the manager frequently in charge of employees and the actual cooking of the burger patties.  This method is opposite of competing fast food restaurants who assign the burger cooking to entry level employees and customer management to higher levels.  In-n-out maintains a smaller menu focusing on a few key items instead of an expansive or seasonally themed menu making it easier to maintain high standards of quality.  Lastly their slow growth and enthusiastic fans provide a positive atmosphere lending itself to people thinking more highly of In-n-out where without this influence might be neutral on the brand.
Question: Where is the best place to view the Northern Lights in Europe?
Answer: In Europe most people travel to Iceland, Gleenland, Norway, Finland or Sweden with the hope of seeing the Northern Lights. The Northern Lights only tend to be visible between the months of September and April each year. Clear weather is required with little cloud coverage to get the best view.
Question: What data are the embeddings trained on?
Evidence: We tokenize the data using Spacy BIBREF10 . We use 300 Dimensional Glove Common Crawl Embeddings (840B Token) BIBREF11 and fine tune them for the task. We experimented extensively with pre-processing variants and our results showed better performance without lemmatization and lower-casing (see supplement for details). We pad each input to 50 words. We train using RMSprop with a learning rate of .001 and a batch size of 512. We add dropout with a drop rate of 0.1 in the final layer to reduce overfitting BIBREF12 , batch size, and input length empirically through random hyperparameter search.
We use 300 Dimensional Glove Common Crawl Embeddings (840B Token) BIBREF11 and fine tune them for the task.
Answer: The answers are shown as follows:
* Common Crawl
Question: How big is the Atlas Moth?
Evidence: The Atlas moth is one of the largest lepidopterans, with a wingspan measuring up to 24 cm (9.4 in) and a wing surface area of about 160 cm2 (≈25 in2). It is only surpassed in wingspan by the white witch (Thysania agrippina) and Attacus caesar, and in wing surface area by the Hercules moth (Coscinocera hercules). As in most silk moths, females are noticeably larger and heavier than males, while males have broader antennae.
Answer: The Atlas Moth has a wingspan measuring up to 24 cm.
Question: Should I take extra fuel when traveling to Alaska?
Answer: There are limited roads in Alaska, as well as northern Canada. While there are some gas stops along the way, options are limited and you might run out of gas in the wilderness. As Alaska is an extremely large state, being stranded in the middle of nowhere is potentially very harmful. It’s a very good idea to take extra fuel when taking a road trip to or through Alaska. Make sure you buy a proper gas can that will not dissolve when in contact with gasoline or diesel.
Question: Which neural machine translation system is used?
Evidence: To demonstrate our method in a black-box setting, we focus our experiments on Google's machine translation system (GMT), accessed through its Cloud API. To test the method on real-world sentences, we consider a monologue from the stand-up comedy show “Sarah Silverman: A Speck of Dust”. The monologue consists of 1,244 English sentences, all by a female speaker conveyed to a plural, gender-neutral audience. Our parallel corpora consists of the 1,244 English sentences from the transcript, and their corresponding Hebrew translations based on the Hebrew subtitles. We translate the monologue one sentence at a time through the Google Cloud API. Eyeballing the results suggest that most of the translations use the incorrect, but default, masculine and singular forms for the speaker and the audience, respectively. We expect that by adding the relevant condition of “female speaking to an audience” we will get better translations, affecting both the gender of the speaker and the number of the audience.
To demonstrate our method in a black-box setting, we focus our experiments on Google's machine translation system (GMT), accessed through its Cloud API.
Answer: The answers are shown as follows:
* Google's machine translation system (GMT)
Question: 5 Best place to visit near Bangalore
Answer: Ooty
Sakeleshpur
Coorg
Udupi
Pondicherry
Question: Why are we like aquariums?
Answer: Aquariums, like zoos, provide fun-filled leisure and entertainment activities that double-up as centres for animal rescue, care and rehabilitation, scientific research, education and conservation.
Question: Who were Fernando Pessoa's main heteronyms?
Evidence: Fernando António Nogueira Pessoa (Portuguese: [fɨɾˈnɐ̃du pɨˈsoɐ]; 13 June 1888 – 30 November 1935) was a Portuguese poet, writer, literary critic, translator, publisher, and philosopher, described as one of the most significant literary figures of the 20th century and one of the greatest poets in the Portuguese language. He also wrote in and translated from English and French.

Pessoa was a prolific writer, and not only under his own name, for he created approximately seventy-five others, of which three stand out, Alberto Caeiro, Álvaro de Campos, and Ricardo Reis. He did not call them pseudonyms because he felt that this did not capture their true independent intellectual life and instead called them heteronyms. These imaginary figures sometimes held unpopular or extreme views.

Pessoa's earliest heteronym, at the age of six, was Chevalier de Pas. Other childhood heteronyms included Dr. Pancrácio and David Merrick, followed by Charles Robert Anon, a young Englishman who became Pessoa's alter ego. In 1905/7, when Pessoa was a student at the University of Lisbon, Alexander Search took the place of Anon. The main reason for this was that, although Search was English, he was born in Lisbon, as was his author. But Search represents a transition heteronym that Pessoa used while searching to adapt to the Portuguese cultural reality. After the republican revolution, in 1910, and consequent patriotic atmosphere, Pessoa created another alter ego, Álvaro de Campos, supposedly a Portuguese naval and mechanical engineer, who was born in Tavira, hometown of Pessoa's ancestors, and graduated in Glasgow. Translator and literary critic Richard Zenith notes that Pessoa eventually established at least seventy-two heteronyms. According to Pessoa himself, there are three main heteronyms: Alberto Caeiro, Álvaro de Campos and Ricardo Reis. Pessoa's heteronyms differ from pen names, because they possess distinct biographies, temperaments, philosophies, appearances, writing styles and even signatures. Thus, heteronyms often disagree on various topics, argue and discuss with each other about literature, aesthetics, philosophy, etc.
Answer: Fernando Pessoa created approximately seventy-five heteronyms, of which three stand out, Alberto Caeiro, Álvaro de Campos, and Ricardo Reis.
Pessoa's heteronyms differ from pen names, because they possess distinct biographies, temperaments, philosophies, appearances, writing styles and even signatures.
Question: Who is the most beautiful lady in the world now
Answer: chiara ferragni . for her intelligence and elegant look
Question: What method does the author propose?
Evidence: Most existing recursive neural network (RvNN) architectures utilize only the structure of parse trees, ignoring syntactic tags which are provided as by-products of parsing. We present a novel RvNN architecture that can provide dynamic compositionality by considering comprehensive syntactic information derived from both the structure and linguistic tags. Specifically, we introduce a structure-aware tag representation constructed by a separate tag-level tree-LSTM. With this, we can control the composition function of the existing word-level tree-LSTM by augmenting the representation as a supplementary input to the gate functions of the tree-LSTM. In extensive experiments, we show that models built upon the proposed architecture obtain superior or competitive performance on several sentence-level tasks such as sentiment analysis and natural language inference when compared against previous tree-structured models and other sophisticated neural models.
We present a novel RvNN architecture that can provide dynamic compositionality by considering comprehensive syntactic information derived from both the structure and linguistic tags.
Answer: They present a novel RvNN architecture that can provide dynamic compositionality by considering comprehensive syntactic information derived from both the structure and linguistic tags.
Question: Extract the names of Jesse LaFollette's grandchildren from the provided passage
Evidence: Jesse LaFollette (1781 NJ-1843 Ind) was the grandfather of Robert Marion La Follette, Sr., William La Follette, and Harvey Marion LaFollette. His family lived next to the Knob Creek Farm, Kentucky owned by Thomas Lincoln during Abraham Lincoln's boyhood years. LaFollette is shown in one of the limestone panels at the Lincoln Boyhood National Memorial in Lincoln City, Indiana.
Answer: Robert Marion La Follette, Sr., William La Follette, and Harvey Marion LaFollette
Question: Where is the post office of Shawboro located?
Evidence: Shawboro is an unincorporated community located in Currituck County, North Carolina, United States.

The area takes its name from Henry Marchmore Shaw.

The post office is located close to the intersection of Shawboro Road (NC 34) and North Indian Town Road (SR 1147). The ZIP Code is 27973. The Shawboro area is covered by three different telephone exchanges: Elizabeth City, Moyock, and Shiloh.

Shawboro is served by Crawford Township fire and rescue services as well as Shawboro Elementary School, a K–5 school with approximately 500 students.

Culong, the Shaw House, and Twin Houses are listed on the National Register of Historic Places.
Answer: The post office of Shawboro, North Carolina is located close to the intersection of NC 34 Shawboro road and North Indian Town Road (SR 1147).
Question: Who is Carol Banawa?
Evidence: Carol Claire Aguilar Banawa-Crisostomo (born March 4, 1981), better known in the Philippines as Carol Banawa, is a US-based Filipina singer, actress, and nurse. She is a Star Magic Batch 4 alumna.
Answer: Carol Claire Aguilar Banawa-Crisostomo (born March 4, 1981), better known in the Philippines as Carol Banawa, is a US-based Filipina singer, actress, and nurse. She is a Star Magic Batch 4 alumna.
Raised in Batangas, she has two siblings, Alexander and Cherry. Banawa started singing when she was a little girl while her family lived in Saudi Arabia. Her family then moved back to the Philippines. There, she was invited to join the new roster of ABS-CBN stars through the children-oriented show Ang TV.
She has performed at the Madison Square Garden in New York City at the 2003 New York Music Festival.

In 2010, she made her comeback in the music industry, and starred in the hit Philippine TV series, Mara Clara, where she sang the opening song of the said TV series. She also covered Till My Heartaches End, the theme song of the 2010 film of the same name.
In 2016, her song "Bakit 'Di Totohanin" was featured in one of the scenes of the U.S. drama series The Vampire Diaries.
Question: In the series A Song of Ice and Fire, who is the founder of House Towers?
Answer: Walton Towers
Question: Would you like to try some Bánh Xèo, a popular Vietnamese disk?
Evidence: Bánh xèo (Vietnamese: [ɓǎjŋ̟ sɛ̂w], lit. 'sizzling pancake') is a crispy, stuffed rice pancake popular in Vietnam. The name refers to the sound (from xèo – 'sizzling') a thin layer of rice batter makes when it is poured into the hot skillet. It is a savoury fried pancake made of rice flour, water, and turmeric powder. It can also be called a Vietnamese crêpe. Some common stuffings include pork, prawns, diced green onion, mung bean, and bean sprouts. Bánh xèo served with sides. Usually, some commonly added ingredients include leafy greens like lettuces or perilla leaves, other herbs as flavor enhancers like mint leaves and Thai basil, cucumbers, and pickled vegetables, usually carrots and radishes. Lastly, its dipping sauce is Nước chấm (sweet and sour garlic fish sauce). Elements of each side and sauce add to the fresh-tasting fried Bánh Xèo.
Answer: Bánh xèo is my favorite quickie food. It's light, but full of flavors.
Question: What is the meaning of the information age
Answer: The Information Age (also known as the Computer Age, Digital Age, Silicon Age, or New Media Age) is a historical period that began in the mid-20th century. It is characterized by a rapid shift from traditional industries, as established during the Industrial Revolution, to an economy centered on information technology. The onset of the Information Age has been linked to the development of the transistor in 1947, the optical amplifier in 1957, and Unix time, which began on January 1, 1970. These technological advances have had a significant impact on the way information is processed and transmitted.

According to the United Nations Public Administration Network, the Information Age was formed by capitalizing on computer microminiaturization advances, which led to modernized information systems and internet communications as the driving force of social evolution.
Question: What's the function of the image classifier that the authors find?
Evidence: We proposed to use visual renderings of documents to capture implicit document quality indicators, such as font choices, images, and visual layout, which are not captured in textual content. We applied neural network models to capture visual features given visual renderings of documents. Experimental results show that we achieve a 2.9% higher accuracy than state-of-the-art approaches based on textual features over Wikipedia, and performance competitive with or surpassing state-of-the-art approaches over arXiv. We further proposed a joint model, combining textual and visual representations, to predict the quality of a document. Experimental results show that our joint model outperforms the visual-only model in all cases, and the text-only model on Wikipedia and two subsets of arXiv. These results underline the feasibility of assessing document quality via visual features, and the complementarity of visual and textual document representations for quality assessment.
We proposed to use visual renderings of documents to capture implicit document quality indicators, such as font choices, images, and visual layout, which are not captured in textual content.
Answer: The authors find that implicit quality indicators, such as images and visual layout, can be captured by an image classifier, at a level comparable to a text classifier.
Question: Where is the explored area coming from (my understanding is that the environment does not provide the explored area)?
Evidence: Affordance-aware navigation is a major challenge in solving complex and long-horizon indoor tasks such as ALFRED with both navigation and object interactions. Specifically, given each object of interest in the scene, the agent is required to not only find and approach it but also end up at a pose (x, y, r, h), that is feasible for subsequent interactions with the object. For instance, to open a fridge, the robot should approach the fridge closely enough (so the door is within reach), look at it (so that the fridge is in the field of view), and leave enough room to open the door. To solve a long-horizon task involving multiple navigation and object interaction subgoals, it is natural to use an explicit semantic map, either 2D or 3D, of the environment (similar to Neural Active SLAM Chaplot et al. (2020a)), together with model-based planning (e.g. as in). This line of work tends to generalize better than models that directly learn mappings from human instructions to navigation & interaction actions (e.g., E.T.). With perfect knowledge of the environment, it is possible to achieve (nearly) perfect performance. In practice, however, the semantic map acquired at inference time is usually far from ideal, primarily due to Incompleteness (missing information due to insufficient exploration of the scene) and Inaccuracy (erroneous object location prediction on the map, especially for small objects).
To improve exploration performance, we propose a multimodal module that, at each step, predicts an exploration action a ∈ {MoveAhead, RotateLeft, RotateRight} by taking visual observations & actions in the past, step-by-step language instructions, and the explored area map which indicates where the agent has visited. We show that, compared to existing model-based approaches on ALFRED (e.g., which applies random exploration), our use of lowlevel language instructions leads to more efficient exploration. The proposed exploration module operates at the subgoal level and only predicts exploration actions (in contrast to E.T. which directly predicts actions for the entire task). The extra modality (the explored area) facilitates exploration by providing the agent with explicit spatial information. We illustrate the exploration module in Figure, elaborate its details in Section 4.3, and empirically demonstrate its advantages in Section 5.
To improve exploration performance, we propose a multimodal module that, at each step, predicts an exploration action a ∈ {MoveAhead, RotateLeft, RotateRight} by taking visual observations & actions in the past, step-by-step language instructions, and the explored area map which indicates where the agent has visited.
Answer: The “explored area” comes from the agent’s prediction of its exploration actions. 
Given such exploration actions, we can directly compute where the agent has visited.
Question: What country has the highest GDP?
Evidence: The United States is a highly developed country, and its economy accounts for approximately a quarter of global GDP and is the world's largest by GDP at market exchange rates. By value, the United States is the world's largest importer and second-largest exporter. Although it accounts for just over 4.2% of the world's total population, the U.S. holds over 30% of the total wealth in the world, the largest share held by any country.
Answer: The United States has the world's largest GDP at market rate exchange rates.  The United States also accounts for approximately 25% of the global GDP.  It is the largest importer and second-largest exporter.  Having only 4.2% of the world's population, the United States holds over 30% of the total wealth in the world, which is the largest share held by one country.
Question: What is the movie Forrest Gump about
Answer: Forrest Gump is a 1994 movie directed by Robert Zemeckis and starring Tom Hanks in the titular role.  The movie follows the life of Forrest, a simple and naive boy as he grows up in Mobile Alabama. Forest unwittingly witnesses or becomes involved in numerous notable events in American history. Forrest fights in the Vietnam War, becomes a global Ping Pong Champion and founds one of the largest Shrimp boating companies in the Nation, among other things.  Forrest Gump is a sweet and nostalgic movie that won numerous awards and remains highly popular.
Question: Please give me the list of airports that are owned by Australia Pacific Airports Corporation.
Evidence: Australia Pacific Airports Corporation Limited (APAC) is an unlisted company and owner of two Australian airports: Melbourne Airport and Launceston Airport. Each airport is operated by an airport lessee company, in which APAC has a controlling interest: Australia Pacific Airports (Melbourne) Pty Ltd and Australia Pacific Airports (Launceston) Pty Ltd respectively.
Answer: Australia Pacific Airports Corporation Limited owns two airports in Australia called Launceston Airport and Melbourne Airport.
Question: What challenges are highlighted?
Evidence: There are two aspects that we defer to future work. First, the systems designed here assumed that the input are valid claim sentences. To make use of such systems, one needs to develop mechanisms to recognize valid argumentative structures. In addition, we ignore trustworthiness and credibility issues, important research issues that are addressed in other works.
There are two aspects that we defer to future work. First, the systems designed here assumed that the input are valid claim sentences. To make use of such systems, one needs to develop mechanisms to recognize valid argumentative structures. In addition, we ignore trustworthiness and credibility issues, important research issues that are addressed in other works.
Answer: The answers are shown as follows:
* one needs to develop mechanisms to recognize valid argumentative structures
* we ignore trustworthiness and credibility issues
Question: How did the team divide the PDTB section partition in their experiment?
Evidence: The Penn Discourse Treebank (PDTB): We experimented with PDTB v2.0 BIBREF7 which is the largest annotated corpus containing 36k discourse relations in 2,159 Wall Street Journal (WSJ) articles. In this work, we focus on the top-level discourse relation senses which are consist of four major semantic classes: Comparison (Comp), Contingency (Cont), Expansion (Exp) and Temporal (Temp). We followed the same PDTB section partition BIBREF12 as previous work and used sections 2-20 as training set, sections 21-22 as test set, and sections 0-1 as development set. Table 1 presents the data distributions we collected from PDTB.
Preprocessing: The PDTB dataset documents its annotations as a list of discourse relations, with each relation associated with its two discourse units. To recover the paragraph context for a discourse relation, we match contents of its two annotated discourse units with all paragraphs in corresponding raw WSJ article. When all the matching was completed, each paragraph was split into a sequence of discourse units, with one discourse relation (implicit or explicit) between each two adjacent discourse units. Following this method, we obtained 14,309 paragraphs in total, each contains 3.2 discourse units on average. Table 2 shows the distribution of paragraphs based on the number of discourse units in a paragraph.
We followed the same PDTB section partition (Rutherford and Xue, 2015) as previous work and used sections 2- 20 as training set, sections 21-22 as test set, and sections 0-1 as development set.
Answer: The team used sections 2- 20 as training set, sections 21-22 as test set, and sections 0-1 as development set.