DataHammer/scimrc huggingface dataset:
Question: Given this paragraph about the domestication of mammals, tell me the earliest known time period in which dairying occurred and also give me the location.
Evidence: Humans first learned to consume the milk of other mammals regularly following the domestication of animals during the Neolithic Revolution or the development of agriculture. This development occurred independently in several global locations from as early as 9000–7000 BC in Mesopotamia to 3500–3000 BC in the Americas. People first domesticated the most important dairy animals – cattle, sheep and goats – in Southwest Asia, although domestic cattle had been independently derived from wild aurochs populations several times since. Initially animals were kept for meat, and archaeologist Andrew Sherratt has suggested that dairying, along with the exploitation of domestic animals for hair and labor, began much later in a separate secondary products revolution in the fourth millennium BC. Sherratt's model is not supported by recent findings, based on the analysis of lipid residue in prehistoric pottery, that shows that dairying was practiced in the early phases of agriculture in Southwest Asia, by at least the seventh millennium BC. From Southwest Asia domestic dairy animals spread to Europe (beginning around 7000 BC but did not reach Britain and Scandinavia until after 4000 BC), and South Asia (7000–5500 BC). The first farmers in central Europe and Britain milked their animals. Pastoral and pastoral nomadic economies, which rely predominantly or exclusively on domestic animals and their products rather than crop farming, were developed as European farmers moved into the Pontic–Caspian steppe in the fourth millennium BC, and subsequently spread across much of the Eurasian steppe. Sheep and goats were introduced to Africa from Southwest Asia, but African cattle may have been independently domesticated around 7000–6000 BC.
Answer: The earliest known dairying occurred between 9000-7000 BC in Mesopotamia.
Question: What evaluation metrics are used?
Evidence: Table TABREF34 shows the performances of the different methods. From the table, we can see that the performances of most tasks can be improved with the help of multi-task learning. FS-MTL shows the minimum performance gain from multi-task learning since it puts all private and shared information into a unified space. SSP-MTL and PSP-MTL achieve similar performance and are outperformed by ASP-MTL which can better separate the task-specific and task-invariant features by using adversarial training. Our proposed models (SA-MTL and DA-MTL) outperform ASP-MTL because we model a richer representation from these 16 tasks. Compared to SA-MTL, DA-MTL achieves a further improvement of INLINEFORM0 accuracy with the help of the dynamic and flexible query vector. It is noteworthy that our models are also space efficient since the task-specific information is extracted by using only a query vector, instead of a BiLSTM layer in the shared-private models.
FLOAT SELECTED: Table 2: Performances on 16 tasks. The column of “Single Task” includes bidirectional LSTM (BiLSTM), bidirectional LSTM with attention (att-BiLSTM) and the average accuracy of the two models. The column of “Multiple Tasks” shows several multi-task models. * is from [Liu et al., 2017] .
Table TABREF34 shows the performances of the different methods.
FLOAT SELECTED: Table 2: Performances on 16 tasks. The column of “Single Task” includes bidirectional LSTM (BiLSTM), bidirectional LSTM with attention (att-BiLSTM) and the average accuracy of the two models. The column of “Multiple Tasks” shows several multi-task models. * is from [Liu et al., 2017] .
Answer: Accuracy on each dataset and the average accuracy on all datasets.
Question: what is north america
Evidence: North America is a continent in the Northern Hemisphere and almost entirely within the Western Hemisphere.
Answer: North America is a continent in the Northern Hemisphere and almost entirely within the Western Hemisphere. It is bordered to the north by the Arctic Ocean, to the east by the Atlantic Ocean, to the southeast by South America and the Caribbean Sea, and to the west and south by the Pacific Ocean. Because it is on the North American Tectonic Plate, Greenland is included as a part of North America geographically.
Question: What did Ralph Agas did as a profession?
Evidence: Ralph Agas (or Radulph Agas) (c. 1540 – 26 November 1621) was an English land surveyor and cartographer. He was born at Stoke-by-Nayland, Suffolk, in about 1540, and lived there throughout his life, although he travelled regularly to London. He began to practise as a surveyor in about 1566, and has been described as "one of the leaders of the emerging body of skilled land surveyors".

Agas is particularly known for his large-scale town map of Oxford (surveyed 1578, published 1588). Early maps of London and Cambridge were also formerly attributed to him, but these attributions are no longer upheld.
Answer: Ralph Agas was an English land surveyor and cartographer, he was born at Stoke-by-Nayland, Suffolk.
Question: What happened at the height of the American revolution?
Evidence: During the height of the American Revolution, in the summer of 1780, British sympathizers (known as Tories) began attacking the outposts of American revolutionaries located along the Susquehanna River in the Wyoming Valley. Because of reports of Tory activity in the region, Captain Daniel Klader and a platoon of 41 men from Northampton County were sent to investigate. They traveled north from the Lehigh Valley along a path known as "Warrior's Trail" (which is present-day Pennsylvania Route 93). This route connects the Lehigh River in Jim Thorpe (formerly known as Mauch Chunk) to the Susquehanna River in Berwick.

Captain Klader's men made it as far north as present-day Conyngham, when they were ambushed by Tory militiamen and members of the Seneca tribe. In all, 15 men were killed on September 11, 1780, in what is now known as the Sugarloaf Massacre.
Answer: In the summer of 1780 Tories also known as British sympathizers started to attack American revolutionaries outposts along a river in the Wyoming valley.  Captain Daniel Klader sent an American Platoon of 41 men to go see what was going on and they ended up getting ambushed by the British sympathizers.  15 men in the platoon were killed in 1780 and this is what is known today as the Sugarloaf Massacre.
Question: What is an API endpoint?
Evidence: Endpoints are important aspects of interacting with server-side web APIs, as they specify where resources lie that can be accessed by third party software. Usually the access is via a URI to which HTTP requests are posted, and from which the response is thus expected. Web APIs may be public or private, the latter of which requires an access token.

Endpoints need to be static, otherwise the correct functioning of software that interacts with it cannot be guaranteed. If the location of a resource changes (and with it the endpoint) then previously written software will break, as the required resource can no longer be found at the same place. As API providers still want to update their web APIs, many have introduced a versioning system in the URI that points to an endpoint.
Answer: Endpoints specify where resources lie that can be accessed by third party software. Clients use endpoints to interact with server-side web APIs.
Question: What is structural biology?
Answer: Structural biology is a field that is many centuries old which, as defined by the Journal of Structural Biology, deals with structural analysis of living material (formed, composed of, and/or maintained and refined by living cells) at every level of organization. Early structural biologists throughout the 19th and early 20th centuries were primarily only able to study structures to the limit of the naked eye's visual acuity and through magnifying glasses and light microscopes.

In the 20th century, a variety of experimental techniques were developed to examine the 3D structures of biological molecules. The most prominent techniques are X-ray crystallography, nuclear magnetic resonance, and electron microscopy. Through the discovery of X-rays and its applications to protein crystals, structural biology was revolutionized, as now scientists could obtain the three-dimensional structures of biological molecules in atomic detail. Likewise, NMR spectroscopy allowed information about protein structure and dynamics to be obtained. Finally, in the 21st century, electron microscopy also saw a drastic revolution with the development of more coherent electron sources, aberration correction for electron microscopes, and reconstruction software that enabled the successful implementation of high resolution cryo-electron microscopy, thereby permitting the study of individual proteins and molecular complexes in three-dimensions at angstrom resolution.

With the development of these three techniques, the field of structural biology expanded and also became a branch of molecular biology, biochemistry, and biophysics concerned with the molecular structure of biological macromolecules (especially proteins, made up of amino acids, RNA or DNA, made up of nucleotides, and membranes, made up of lipids), how they acquire the structures they have, and how alterations in their structures affect their function. This subject is of great interest to biologists because macromolecules carry out most of the functions of cells, and it is only by coiling into specific three-dimensional shapes that they are able to perform these functions. This architecture, the "tertiary structure" of molecules, depends in a complicated way on each molecule's basic composition, or "primary structure." At lower resolutions, tools such as FIB-SEM tomography have allowed for greater understanding of cells and their organelles in 3-dimensions, and how each hierarchical level of various extracellular matrices contributes to function (for example in bone). In the past few years it has also become possible to predict highly accurate physical molecular models to complement the experimental study of biological structures. Computational techniques such as Molecular Dynamics simulations can be used in conjunction with empirical structure determination strategies to extend and study protein structure, conformation and function.
Question: What are dividends?
Answer: A dividend is paid as a percentage on the price of an individual stock.  It can be paid out quarterly, monthly, or yearly.  It's a payment or distribution of earning from a company paid to shareholders and it is approved by the company's board of directors.  It can be paid out as a cash payment or in company stock.
Question: Which of these fruits, apple, strawberry, tomato, orange, cherry, grape; would be a poor choice to end a line in a song lyric with?
Answer: While all the items listed are indeed fruits, the worst fruit to use to end a line in a song lyric is the "orange" because it has no rhymes unless you're the exceptional Eminem wom can rhyme any word, including orange.
Question: What languages do they investigate for machine translation?
Evidence: We use English translations of the Chinese source texts in the WMT 2017 English–Chinese test set BIBREF18 for all experiments presented in this article:
We use English translations of the Chinese source texts in the WMT 2017 English–Chinese test set BIBREF18 for all experiments presented in this article:
Answer: The answers are shown as follows:
* English 
* Chinese
Question: In knowledge distillation or model compression, analysis on different architectures is required. However, in this submission, the large network is fixed as ResNet-50 and the compact network is fixed as ResNet-18. What's the reason?
Evidence: To show that STU-KD is applicable to different network architectures, two additional experiments are conducted. In the first experiment, Proxyless-Mobile (Cai et al., 2019) is selected as the compact model, and ResNet-50 (He et al., 2016) is selected as the large source model. The results are shown in Table 6. In the second group, ResNet-34 is selected as the compact model, and the ResNet-101 is selected as the large source model. The results are shown in Table 7.
Answer: We will conduct two additional groups of experiments for the analysis on different network architectures. In the first group, ResNet-101 is selected as the large model, and ResNet-34 is selected as the compact model; in the second group, ResNet-50 is selected as the large model, and Proxyless-Mobile [2] is selected as the compact model.
Question: Is the saying "An Apple a Day Keeos the Doctor Away" Factually correct?
Answer: The above saying is factually incorrect. Just apple in itself although healthy might just not be sufficient. Although it is highly recommended to incorporate at least 1 cup of fruit in your daily meal.
Question: Identify which car manufacturer is German or American: Opel, GMC
Answer: Opel is German, GMC is American
Question: Best place to visit for a day from Bangalore
Answer: 1. Myshore
2. Coorg
3. Ooty
Question: What is used by them to fit the embedding and context vectors?
Evidence: We use stochastic gradient descent with Adagrad BIBREF10 to fit the embedding and context vectors. Following BIBREF1 , we reduce the computational complexity by splitting the gradient into two terms. The first term contains the non-zero entries ( INLINEFORM0 ); the second term contains the zero entries ( INLINEFORM1 ). We compute the exact gradient for the non-zero points; We subsample for the zero data points. This is similar to negative sampling BIBREF5 , which also down-weights the contributions of the zero points. Unlike BIBREF1 which uses INLINEFORM2 regularization to protect against overfitting when fitting the embedding vectors we use early stopping based on validation accuracy, for the same effect.
We use stochastic gradient descent with Adagrad (Duchi et al., 2011) to fit the embedding and context vectors.
Answer: Stochastic gradient descent with Adagrad(Duchi et al., 2011) .
Question: What kind of support does sequence to sequence models provide for the growth of the task of generating natural language descriptions of structured data?
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:
The task of generating natural language descriptions of structured data (such as tables) (Kukich, 1983; McKeown, 1985; Reiter and Dale, 1997) 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 (Lebret et al., 2016; Wiseman et al., 2017; Novikova et al., 2017b; Gardent et al., 2017).
Answer: Sequence to sequence models provide an easy way of encoding tables and generating text from them.
Question: What is Google Sheets and how does it compatible with Microsoft Excel?
Evidence: Google Sheets is a spreadsheet program included as part of the free, web-based Google Docs Editors suite offered by Google. Google Sheets is available as a web application, mobile app for: Android, iOS, Microsoft Windows, BlackBerry OS and as a desktop application on Google's ChromeOS. The app is compatible with Microsoft Excel file formats. The app allows users to create and edit files online while collaborating with other users in real-time. Edits are tracked by a user with a revision history presenting changes. An editor's position is highlighted with an editor-specific color and cursor and a permissions system regulates what users can do. Updates have introduced features using machine learning, including "Explore", offering answers based on natural language questions in a spreadsheet. This is one of the services provided by Google that also includes Google Docs, Google Slides, Google Drawings, Google Forms, Google Sites and Google Keep.
Answer: Google Sheets is a spreadsheet program included as part of the free, web-based Google Docs Editors suite offered by Google and is compatible with Microsoft Excel file formats (e.g., .XLS, .XLSX, .CSV, etc., . . .).
Question: How do the authors initialize their embedding matrix?
Evidence: Visual dialog BIBREF0 is an interesting new task combining the research efforts from Computer Vision, Natural Language Processing and Information Retrieval. While BIBREF1 presents some tips and tricks for VQA 2.0 Challenge, we follow their guidelines for the Visual Dialog challenge 2018. Our models use attention similar to BIBREF2 to get object level image representations from Faster R-CNN model BIBREF3. We experiment with different encoder mechanisms to get representations of conversational history.
Common to all the models, we initialize our embedding matrix with pre-trained Glove word vectors of 300 dimensions using 6B tokens .
Answer: Initialize embedding matrix with pre-trained Glove word vectors of 300 dimensions using 6B tokens.
Question: What are Flos
Answer: Flos is a genus of butterflies in the family Lycaenidae. The species of this genus are commonly known as plushblues and are found in the Indomalayan realm.
Question: How can we cool the planet?
Answer: One way to cool the planet is to reduce the amount of greenhouse gases in the atmosphere. This can be done by reducing the use of fossil fuels, increasing the use of renewable energy sources, and reducing waste. Additionally, we can also reduce our reliance on air conditioning and other energy-intensive activities.
Question: What do the new datasets introduced by authors use for?
Evidence: It is well-established that gender bias exists in language – for example, we see evidence of this given the prevalence of sexism in abusive language datasets BIBREF0, BIBREF1. However, these are extreme cases of gender norms in language, and only encompass a small proportion of speakers or texts.
Less studied in NLP is how gender norms manifest in everyday language – do people talk about women and men in different ways? These types of differences are far subtler than abusive language, but they can provide valuable insight into the roots of more extreme acts of discrimination. Subtle differences are difficult to observe because each case on its own could be attributed to circumstance, a passing comment or an accidental word. However, at the level of hundreds of thousands of data points, these patterns, if they do exist, become undeniable. Thus, in this work, we introduce new datasets and methods so that we can study subtle gender associations in language at the large-scale.
Our contributions include:
Two datasets for studying language and gender, each consisting of over 300K sentences.
Methods to infer gender-associated words and labeled clusters in any domain.
Novel findings that demonstrate in both domains that people do talk about women and men in different ways.
Each contribution brings us closer to modeling how gender associations appear in everyday language. In the remainder of the paper, we present related work, our data collection, methods and findings, and human evaluations of our system.
Thus, in this work, we introduce new datasets and methods so that we can study subtle gender associations in language at the large-scale.
Answer: For studying subtle gender associations in language at the large-scale by using the new datasets.
Question: Give me some ideas on how to grow tomatoes in my back yard.
Answer: 1. Plant tomatoes directly in the ground with a support system like a trellis
2. Plant tomatoes in a raised bed with support cages around each plant
3. Place tomatoes in individual pots, use the string method to support tomatoes
Question: What are the primary characteristics of pluralism (also known as interest group liberalism or polyarchy)? What are the main criticisms of this theory?
Answer: Robert Dahl argues that interest group liberalism dominants power in the United States.  This is where non-cumulative inequalities, manifested by multiple groups that each have strengths and weaknesses, fight for political power.  Groups form to represent constituencies, where leaders are elected and engage in compromise decision-making within their group and with leaders of other groups. Groups with opposing interests prevent the accumulation of power with one group.
Critics of this theory argue that Dahl only talked about policy decisions that were openly debated.  There is a private or hidden power struggle where it is decided whether or not to consider policy at all. Second, that there are cumulative inequalities where those with a low level of resources are not able to mobilize and represent their own interests. Lastly, a group's leadership does not always represent the rank and file membership of the group as a whole.
Question: What are 5 easy dinner ideas that kids will like?
Answer: Macaroni and cheese, chicken nuggets, ramen noodles, chicken and potato soup, grilled cheese sandwiches