DataHammer/scimrc huggingface dataset:
Question: Tell me the awards that Zhu won and the year that she won them in the following format: {Award}: {Year}
Evidence: Zhu's works, most related to home, travel, explore and strangeness, have been published in magazines and shown at photography festival internationally, including the FORMAT International Festival and Lianzhou International Photo Festival. Her photobook was selected as for the PHOTOEYE's Best Books of 2012. She also won the Three Shadows Photography Award in 2014 and the Barcelona International Photography Awards in 2015.

When Zhu was in secondary school, she was more interested in the village she lived in, especially the old houses going to disappear. Thus, she started photographing them and that was the first time she picked up her grandfather's camera and created something. At the time that digital camera being popular, her parent bought her one which was a Taiwan brand called PREMIER.
Answer: Here is a list of awards that Zhu won and the year in which she won them:

PHOTOEYE's Best Books of 2012: 2012
Three Shadows Photography Award: 2014
Barcelona International Photography Awards: 2015
Question: My heating bill is too high.  How can I lower it?  Give me three suggestions.
Answer: (1) You can insulate your house better.  This can often be done cheaply, such as by covering your windows with plastic during the winter.  You can also invest in permanent insulation such as double-paned windows and new attic insulation.
(2) You can wear warmer clothing and turn down the heat.  It's not too bad to bundle up during the winter!
(3) You can invest in a heat pump.  Heat pumps are more energy-efficient than traditional heaters.
Question: Identify which animal species is alive or extinct: Tasmanian Tiger, Macaw
Answer: Macaw is alive, Tasmanian Tiger is extinct.
Question: How is validation of the data performed?
Evidence: A maximum of three contributors will listen to any audio clip. If an $<$audio,transcript$>$ pair first receives two up-votes, then the clip is marked as valid. If instead the clip first receives two down-votes, then it is marked as invalid. A contributor may switch between recording and validation as they wish.
Only clips marked as valid are included in the official training, development, and testing sets for each language. Clips which did not recieve enough votes to be validated or invalidated by the time of release are released as “other”. The train, test, and development sets are bucketed such that any given speaker may appear in only one. This ensures that contributors seen at train time are not seen at test time, which would skew results. Additionally, repetitions of text sentences are removed from the train, test, and development sets of the corpus.
A maximum of three contributors will listen to any audio clip. If an $<$audio,transcript$>$ pair first receives two up-votes, then the clip is marked as valid. If instead the clip first receives two down-votes, then it is marked as invalid. A contributor may switch between recording and validation as they wish.
Only clips marked as valid are included in the official training, development, and testing sets for each language. Clips which did not recieve enough votes to be validated or invalidated by the time of release are released as “other”. The train, test, and development sets are bucketed such that any given speaker may appear in only one. This ensures that contributors seen at train time are not seen at test time, which would skew results. Additionally, repetitions of text sentences are removed from the train, test, and development sets of the corpus.
Answer: The answers are shown as follows:
* A maximum of three contributors will listen to any audio clip. If an $<$audio,transcript$>$ pair first receives two up-votes, then the clip is marked as valid. If instead the clip first receives two down-votes, then it is marked as invalid.
Question: Identify the bird from the list: Bar-tailed godwit, Leopard, Shark
Answer: Bar-tailed godwit
Question: What’s your favorite way to spend a day off?
Answer: My favorite way to spend a day off is to spend it with my family and friends. I love to take long walks with my dog, go for bike rides, and spend time outdoors with my family. I also love to read, write, and catch up on my favorite shows.
Question: What may be leveraged by the candidate-generating parser?
Evidence: We present an information extraction architecture that augments a candidate-generating parser with a deep neural network. The candidate-generating parser may leverage constraints. At the same time, the architecture gains the neural networks's ability to leverage large amounts of data to learn complex features that are tuned for the application at hand. Our method assumes the existence of a potentially noisy source of supervision INLINEFORM0 , e.g. via consistency checks of extracted data against existing databases, or via human interaction. This supervision is used to train the neural network.
Our extraction system has three advantages over earlier work on information extraction with deep neural networks BIBREF2 , BIBREF3 , BIBREF4 , BIBREF5 , BIBREF6 , BIBREF7 , BIBREF8 , BIBREF9 :
Our system leverages “free” data to train a deep neural network, and does not require large-scale manual annotation. The network is trained with noisy supervision provided by measures of consistency with existing databases (e.g. an extraction ts_tick_abs (US_Unemployment, 49%) would be implausible given recent US employment history). With slight modifications, our pipeline could be trained with supervision from human interaction, such as clicks on online advertisements. Learning without explicit annotations is critical in applications where large-scale manual annotation would be prohibitively expensive.
If an extractor for the given application has already been built, the neural network boosts its accuracy without the need to re-engineer or discard the existing solution. Even for new systems, the decoupling of candidate-generation and the neural network offers advantages: the candidate-generating parser can easily enforce contraints that would be difficult to support in an algorithm relying entirely on a neural network. Note that, in particular, a carefully engineered candidate-generating parser enforces constraints intelligently, and can in many instances eliminate the need to evaluate computationally expensive constraints, e.g. API calls.
We encode the candidate-generating parser's document annotations character-by-character into vectors INLINEFORM0 that also include a one-hot encoding of the character itself. We believe that this encoding makes it easier for the network to learn character-level characteristics of the entities in the semantic relation. Moreover, our encoding lends itself well to processing both by recurrent architectures (processing character-by-character input vectors INLINEFORM1 ) and convolutional architectures (performing 1D convolutions over an input matrix whose columns are vectors INLINEFORM2 ).
In a production setting, the neural architecture presented here reduced the number of false positive extractions in financial information extraction application by INLINEFORM0 relative to a mature system developed over the course of several years.
The candidate-generating parser may leverage constraints.
Answer: Constraints
Question: Does the author mention any challenges faced when deploying such a software pipeline is presented?
Evidence: The following sections outline the multiple aspects that go into building a near-real-time pipeline for the creation of political event data. First, I provide a discussion of the considerations that went into the architecture of the software used to create the data. Next, I outline the various advances that have been made in the data collection and processing steps. Finally, a discussion of the challenges and obstacles faced when deploying such a software pipeline is presented.
The following sections outline the multiple aspects that go into building a near-real-time pipeline for the creation of political event data. First, I provide a discussion of the considerations that went into the architecture of the software used to create the data. Next, I outline the various advances that have been made in the data collection and processing steps. Finally, a discussion of the challenges and obstacles faced when deploying such a software pipeline is presented.
Answer: Yes.
Question: What is separation anxiety in dogs?
Evidence: Separation anxiety in dogs describes a condition in which a dog exhibits distress and behavior problems when separated from its handler. Separation anxiety typically manifests within minutes of departure of the handler. It is not fully understood why some dogs suffer from separation anxiety and others do not. The diagnosis process often leads to a misdiagnosis as it is difficult to differentiate from other medical and behavioral problems. The behavior may be secondary to an underlying medical condition. With chronic stress, impairments to physiological health can manifest. Increased stress in the dog alters hormone levels, thus decreasing natural immunity to various health problems.

Signs and symptoms
Dogs suffering from separation anxiety typically exhibit these behaviors:

Following handler excessively
Pacing
Excessive salivating
Excessive shaking (usually seen in smaller breeds like the Chihuahua and Yorkshire Terrier)
Vomiting
Destructive chewing
Barking, howling, whining
Urination, defecation in the house
Coprophagia
Self harm
Digging and scratching at doors or windows in an attempt to reunite with the handler
Escaping
Anorexia
Overactivity (excessive greeting, restlessness)
Cause

The cause of dog separation anxiety is unknown, but may be triggered by:

a traumatic event
a change in routine
major life change (e.g., new home, new baby, death of a family member, abandonment to a shelter)
extreme attachment or dependency on the owner
Answer: Separation anxiety in dogs describes a condition in which a dog exhibits distress and behavior problems when separated from its handler. It can be triggered by traumatic events such as being bitten by other dogs, being mistreated, changes in routes, and major life changes such as new pets or children being added to the family.

It it is not fully understood why some dogs suffer from separation anxiety. The diagnosis process often leads to a misdiagnosis as it is difficult to differentiate from other medical and behavioral problems. The behavior may be secondary to an underlying medical condition. With chronic stress, impairments to physiological health can manifest. Increased stress in the dog alters hormone levels, thus decreasing natural immunity to various health problems.
Question: What are the primary uses of horses according to the text?
Evidence: Horses and humans interact in a wide variety of sport competitions and non-competitive recreational pursuits as well as in working activities such as police work, agriculture, entertainment, and therapy. Horses were historically used in warfare, from which a wide variety of riding and driving techniques developed, using many different styles of equipment and methods of control. Many products are derived from horses, including meat, milk, hide, hair, bone, and pharmaceuticals extracted from the urine of pregnant mares. Humans provide domesticated horses with food, water, and shelter as well as attention from specialists such as veterinarians and farriers.
Answer: Horses can be used for recreational activities and therapy as well as working activities like police work or agriculture. Historically horses were also used in warfare. Horses can also provide products like meat, milk, hide, hair, bone or pharmaceuticals.
Question: Tell me about the inversion in postcolonial theory
Evidence: The term derives from studies of modalities of resistance by the Subaltern Studies school, but reflects concerns pervasive from the earliest days of post- and anti-colonial writing. Ranajit Guha refers to inversion as one of the modalities of peasant revolt in colonial India, noting practices such as forcing landlords to carry peasants on Sedan chairs. Frantz Fanon's The Wretched of the Earth (1961) provides an extensive discussion and partial advocacy of inversion in a social context defined by strong binaries. A reversal of the coloniser's monopoly on violence is taken to be necessary to break out of the master–slave dialectic, a learnt sense of cultural inferiority and the learned helplessness of the colonised. The term "inversion woodcuts" also appears in peasant studies as a description of imagery such as an ox killing a butcher (e.g. James Scott, Domination and the Arts of Resistance, 166-72).

The term has become useful as a way of theorising violence. Definitions of terms such as racism and sexism are contested, and theorists who use structural or institutional definitions thus refuse to typify actions against members of structurally dominant groups by structurally subordinate groups, or prejudicial beliefs against members of dominant groups, with these terms. Actions such as Palestinian suicide bombing, the 9/11 attacks, land reform in Zimbabwe, the writings and actions of Valerie Solanas and SCUM, and what are treated by the state as racially motivated crimes against white people, would be examples of cases where the term would be used. Ward Churchill's essay On the Justice of Roosting Chickens is an example of this kind of analysis from an author sympathetic to inversion.

Attaching positive values to an essence of the oppressed, as in some black-consciousness and Afrocentric ideas, would also be an instance of inversion, especially to critics. Edward Said argues against this inversion, suggesting that "in Post-colonial national states, the liabilities of such essences as the Celtic spirit, négritude, or Islam are clear: they have much to do not only with the native manipulators, who also use them to cover up contemporary faults, corruptions, tyrannies, but also with the embattled imperial contexts out of which they came and in which they were felt to be necessary" (Culture and Imperialism  16).
Answer: The term derives from studies of modalities of resistance by the Subaltern Studies school, but reflects concerns pervasive from the earliest days of post- and anti-colonial writing. 

Ranajit Guha refers to inversion as one of the modalities of peasant revolt in colonial India, noting practices such as forcing landlords to carry peasants on Sedan chairs.
Question: What models do they use in their built QA system?
Evidence: Recent work on sequence-to-sequence neural networks have shown remarkable progress in many domains such as speech recognition, computer vision and language processing. These neural models can be used to map a sequence to another sequence, which has direct applications in natural language understanding BIBREF0 . One of the major advantages of this framework is that it requires a limited amount of feature engineering while still improving state-of-the-art results. This allows researchers to work on tasks for which domain knowledge may not be available. Question answering (QA) systems can directly benefit from this novel approaches, because it only requires mapping between questions and their answers. Due to the complexity of this mapping, most of the previous research in this domain used a complex pipeline of conventional linguistically-based NLP techniques, such as parsing, part-of-speech tagging and co-reference resolution BIBREF1 .
In this work, we build an open-domain QA system with sequence-to-sequence neural network models. The system was trained with question-answer pairs on the world knowledge represented in the DBpedia repository. Although building an open-domain system allows us to use an extensive amount of data stored in DBpedia, one of the challenges is to store this large amount of knowledge in the neural network architecture. Although these systems generally involve a smaller learning pipeline, they require a significant amount of training data.
Figure FIGREF1 illustrates how a sequence-to-sequence neural network can be trained on question-answering pairs. First, an sequence-to-sequence framework reads the source sentence, i.e. question, using an encoder to build a dense vector, a sequence of non-zero values that represents the meaning of a question. A decoder, processes this vector to predict an answer. In this manner, these encoder-decoder models can capture long-range dependencies in languages, e.g., gender agreements or syntax structures.
In this work, we build an open-domain QA system with sequence-to-sequence neural network models.
Answer: Sequence-to-sequence neural network models.
Question: What is it like be a father?
Answer: Being a father is an experience that will fill you with a terrific sense of wonderment, purpose, and love. It's an experience that goes by entirely too fast, yet also sometimes too slow. Being a father is the pinnacle of our lives and nothing will ever come close to that experience and the achievement that it awards to those who hold it with sacred regard.
Question: When talking about adjectives to describe proximity, which of these words fit into a 'near' category, and which are 'far'. Miles, close, neighbouring, distant, remote, adjacent, adjoining, outlying.
Answer: Close, neighbouring, adjacent and adjoining are adjectives describing a 'near' proximity. Miles, distant, remote and outlying are adjectives describing a 'far' proximity.
Question: Based on this passage, please provide a bullet-point list of the processes used to prepare semiconducting materials for integrated circuits (ICs).
Evidence: There is a combination of processes that are used to prepare semiconducting materials for ICs. One process is called thermal oxidation, which forms silicon dioxide on the surface of the silicon. This is used as a gate insulator and field oxide. Other processes are called photomasks and photolithography. This process is what creates the patterns on the circuit in the integrated circuit. Ultraviolet light is used along with a photoresist layer to create a chemical change that generates the patterns for the circuit.

The etching is the next process that is required. The part of the silicon that was not covered by the photoresist layer from the previous step can now be etched. The main process typically used today is called plasma etching. Plasma etching usually involves an etch gas pumped in a low-pressure chamber to create plasma. A common etch gas is chlorofluorocarbon, or more commonly known Freon. A high radio-frequency voltage between the cathode and anode is what creates the plasma in the chamber. The silicon wafer is located on the cathode, which causes it to be hit by the positively charged ions that are released from the plasma. The result is silicon that is etched anisotropically.

The last process is called diffusion. This is the process that gives the semiconducting material its desired semiconducting properties. It is also known as doping. The process introduces an impure atom to the system, which creates the p–n junction. To get the impure atoms embedded in the silicon wafer, the wafer is first put in a 1,100 degree Celsius chamber. The atoms are injected in and eventually diffuse with the silicon. After the process is completed and the silicon has reached room temperature, the doping process is done and the semiconducting material is ready to be used in an integrated circuit.
Answer: -Thermal oxidation
-Photomasks/photolithography
-Etching (mainly plasma etching)
-Diffusion/doping
Question: Who did the first major work applying deep-learning techniques to text comprehension?
Evidence: A first major work applying deep-learning techniques to text comprehension was Hermann et al. BIBREF1 . This work was followed by the application of Memory Networks to the same task BIBREF2 . Later three models emerged around the same time BIBREF3 , BIBREF4 , BIBREF5 including our psr model BIBREF4 . The AS Reader inspired several subsequent models that use it as a sub-component in a diverse ensemble BIBREF8 ; extend it with a hierarchical structure BIBREF6 , BIBREF24 , BIBREF7 ; compute attention over the context document for every word in the query BIBREF10 or use two-way context-query attention mechanism for every word in the context and the query BIBREF11 that is similar in its spirit to models recently proposed in different domains, e.g. BIBREF25 in information retrieval. Other neural approaches to text comprehension are explored in BIBREF9 , BIBREF12 .
A first major work applying deep-learning techniques to text comprehension was Hermann et al. (Hermann et al., 2015). This work was followed by the application of Memory Networks to the same task (Hill et al., 2015).
Answer: Hermann et al. .
Question: When should I take vitamin D?
Evidence: The UK National Health Service (NHS) recommends that people at risk of vitamin D deficiency, breast-fed babies, formula-fed babies taking less than 500 ml/day, and children aged 6 months to 4 years, should take daily vitamin D supplements throughout the year to ensure sufficient intake. This includes people with limited skin synthesis of vitamin D, who are not often outdoors, are frail, housebound, living in a care home, or usually wearing clothes that cover up most of the skin, or with dark skin, such as having an African, African-Caribbean or south Asian background. Other people may be able to make adequate vitamin D from sunlight exposure from April to September. The NHS and Public Health England recommend that everyone, including those who are pregnant and breastfeeding, consider taking a daily supplement containing 10 μg (400 IU) of vitamin D during autumn and winter because of inadequate sunlight for vitamin D synthesis.
Answer: If you live in England, NHS recommends that people with vitamin D deficiency take supplements, other people should get vitamin D directly from the sun from April to September and take a supplement containing 10 μg (400 IU) of vitamin D during autumn and winter.
Question: What is the largest state in the United States?
Answer: Alaska is the largest state in the United States, trailed by Texas in second place. Alaska has 665,400 square miles of land whereas Texas has 268,597 square miles of land. If Alaska were to be cut in half, Texas would be the third largest state.
Question: According to his business card what job did Al Capone do
Answer: Sell second hand
furniture
Question: Classify each of these as either a green fruit or a yellow fruit: kiwi, banana, granny smith apple, starfruit, grape
Answer: Green fruit: kiwi, granny smith apple, grape
Yellow fruit: Banana, starfruit
Question: What algorithm can be adopted to efficiently solve the training and decoding of the CRF layer?
Evidence: Data analysis and many linguistic studies BIBREF11 , BIBREF33 , BIBREF34 , BIBREF35 have repeatedly shown that discourse relations feature continuity and patterns (e.g., a temporal relation is likely to be followed by another temporal relation). Especially, BIBREF11 firstly reported that patterns exist between implicit discourse relations and their neighboring explicit discourse relations.
Motivated by these observations, we aim to improve implicit discourse relation detection by making use of easily identifiable explicit discourse relations and taking into account global patterns of discourse relation distributions. Specifically, we add an extra CRF layer at the top of the softmax prediction layer (shown in figure 3 ) to fine-tune predicted discourse relations by considering their inter-dependencies.
The Conditional Random Fields BIBREF36 (CRF) layer updates a state transition matrix, which can effectively adjust the current label depending on proceeding and following labels. Both training and decoding of the CRF layer can be solved efficiently by using the Viterbi algorithm. With the CRF layer, the model jointly assigns a sequence of discourse relations between each two adjacent discourse units in a paragraph, including both implicit and explicit relations, by considering relevant discourse unit representations as well as global discourse relation patterns.
Both training and decoding of the CRF layer can be solved efficiently by using the Viterbi algorithm.
Answer: Viterbi algorithm.