DataHammer/scimrc huggingface dataset:
Question: What is the essence of utilitarianism?
Evidence: Utilitarianism is a consequentialist approach to normative ethics that holds morally right actions are those that promote the most human happiness. Jeremy Bentham, who created his version of the theory in 1829, and John Stuart Mill who made his in 1861 are considered the founders of utilitarianism, though the basic concept predates either of the two philosophers. Utilitarianism remains as one of the more appealing and compelling approaches to normative ethics.
Answer: Utilitarianism evaluates any action in terms of the amount of human happiness delivered as the result of the action.
Question: From the passage provided, extract the list of Indian winners of the Academy Awards. Separate them with a comma.
Evidence: At the 30th Academy Awards, Mehboob Khan's 1957 Hindi-language film Mother India was India's first submission for the Academy Award for Best International Feature Film category. It was nominated alongside four other films and lost to the Italian film Nights of Cabiria (1957) by one vote. In 1982, The National Film Development Corporation of India was instrumental in co-producing Richard Attenborough's biographical film Gandhi. At the 55th Academy Awards, Bhanu Athaiya became the first Indian to win an Academy Award for designing the costumes. Ravi Shankar was nominated for Best Original Score for the same film. As of 2023, three Indian films have been nominated for Best International Feature—Mother India, Salaam Bombay! (1988) and Lagaan (2001).

In 1992, legendary Bengali filmmaker Satyajit Ray was bestowed with an Honorary Academy Award, becoming the only Indian to date to receive the honour. Resul Pookutty and A. R. Rahman won the Academy Award for Best Sound Mixing and Best Original Score, respectively, for the 2008 British film Slumdog Millionaire. Rahman also won for Best Original Song alongside lyricist Gulzar for the song "Jai Ho", becoming the first Indian to date to have won more than one Academy Award. Rahman also holds the record for most nominations for an Indian with five total nominations to date, followed by Ismail Merchant with four nominations (three for Best Picture and once for Live Action Short).
Answer: Bhanu Athaiya, Resul Pookutty , A. R. Rahman
Question: How many representative tasks do the authors evaluate DWE on?
Evidence: Word embeddings are fixed-length vector representations for words BIBREF0 , BIBREF1 . In recent years, the morphology of words is drawing more and more attention BIBREF2 , especially for Chinese whose writing system is based on logograms.
UTF8gbsn With the gradual exploration of the semantic features of Chinese, scholars have found that not only words and characters are important semantic carriers, but also stroke feature of Chinese characters is crucial for inferring semantics BIBREF3 . Actually, a Chinese word usually consists of several characters, and each character can be further decomposed into a stroke sequence which is certain and changeless, and this kind of stroke sequence is very similar to the construction of English words. In Chinese, a particular sequence of strokes can reflect the inherent semantics. As shown in the upper half of Figure FIGREF3 , the Chinese character “驾" (drive) can be decomposed into a sequence of eight strokes, where the last three strokes together correspond to a root character “马" (horse) similar to the root “clar" of English word “declare" and “clarify".
Moreover, Chinese is a language originated from Oracle Bone Inscriptions (a kind of hieroglyphics). Its character glyphs have a spatial structure similar to graphs which can convey abundant semantics BIBREF4 . Additionally, the critical reason why Chinese characters are so rich in morphological information is that they are composed of basic strokes in a 2-D spatial order. However, different spatial configurations of strokes may lead to different semantics. As shown in the lower half of Figure 1, three Chinese characters “入" (enter), “八" (eight) and “人" (man) share exactly a common stroke sequence, but they have completely different semantics because of their different spatial configurations.
In addition, some biological investigations have confirmed that there are actually two processing channels for Chinese language. Specifically, Chinese readers not only activate the left brain which is a dominant hemisphere in processing alphabetic languages BIBREF5 , BIBREF6 , BIBREF7 , but also activate the areas of the right brain that are responsible for image processing and spatial information at the same time BIBREF8 . Therefore, we argue that the morphological information of characters in Chinese consists of two parts, i.e., the sequential information hidden in root-like strokes order, and the spatial information hidden in graph-like character glyphs. Along this line, we propose a novel Dual-channel Word Embedding (DWE) model for Chinese to realize the joint learning of sequential and spatial information in characters. Finally, we evaluate DWE on two representative tasks, where the experimental results exactly validate the superiority of DWE in capturing the morphological information of Chinese.
Finally, we evaluate DWE on two representative tasks, where the experimental results exactly validate the superiority of DWE in capturing the morphological information of Chinese.
Answer: Two.
Question: What is the major source of income in Ethiopia and why its important?
Answer: Agriculture is the backbone of the economy and the main source of livelihood for the majority of the population. However, traditional agricultural practices have led to soil degradation and deforestation. Farmers in Ethiopia often rely on a few staple crops, such as teff, wheat, and maize, which are grown repeatedly on the same plot of land without proper rotation or replenishment of soil nutrients (International Labour Organization). This leads to reduced yields, which can make it difficult for farmers to produce enough food to feed their families and earn a living. Deforestation, which is also a major problem, has been driven by the need for more land to grow crops. Ethiopia has one of the highest deforestation rates in the world, with an estimated loss of 1.1 million hectares of forest every year (World Bank).
Question: What medicine is inside of an EpiPen?
Answer: Epinephrine (adrenaline)
Question: What is core banking?
Answer: Core banking is a banking service provided by a group of networked bank branches where customers may access their bank account and perform basic transactions from any of the member branch offices.

Core banking is often associated with retail banking and many banks treat the retail customers as their core banking customers. Businesses are usually managed via the corporate banking division of the institution. Core banking covers basic depositing and lending of money.

Core banking functions will include transaction accounts, loans, mortgages and payments. Banks make these services available across multiple channels like automated teller machines, Internet banking, mobile banking and branches.

Banking software and network technology allows a bank to centralise its record keeping and allow access from any location.
Question: Classify each of the following as a new world or old world crop: Potato, Corn, Tomato, Wheat, Oat, Cacao, Apple, Olive
Answer: Potato: New World, Corn: New World, Tomato: New World, Wheat: Old World, Oat: Old World, Cacao: New World, Apple: Old World, Olive: Old World
Question: Who is the Chinese Li Xueju
Evidence: Li Xueju (simplified Chinese: 李学举; traditional Chinese: 李學舉; pinyin: Lǐ Xuéjǔ; born April 1945) is a politician of the People's Republic of China, and the former Minister of Civil Affairs of PRC.

Born in Gongzhuling, Jilin Province, Li joined the Chinese Communist Party in January 1966, and started working in May 1966. In early years, he served in various posts in local commune. In 1975, he was promoted to Secretary of Communist Youth League committee in Siping region of Jilin. From 1978, he served as vice section chief, vice director and later, director of organization department of CYL central committee. From 1984 to 1986, he studied at CCP Central Party School. In 1986, he was appointed as the director of general office of CYL central committee. He was a member of 10th CYL central committee, and a standing member of 11th and 12th CYL central committee.
Answer: Li Xueju born April 1945 is a politician of the People's Republic of China, and the former Minister of Civil Affairs of PRC.

Born in Gongzhuling, Jilin Province, Li joined the Chinese Communist Party in January 1966, and started working in May 1966. In early years, he served in various posts in local commune. In 1975, he was promoted to Secretary of Communist Youth League committee in Siping region of Jilin. 

From 1978, he served as vice section chief, vice director and later, director of organization department of CYL central committee. From 1984 to 1986, he studied at CCP Central Party School. In 1986, he was appointed as the director of general office of CYL central committee. He was a member of 10th CYL central committee, and a standing member of 11th and 12th CYL central committee.
Question: Which is an imperial or a metric measurement: ton, tonne
Answer: ton is imperial, tonne is metric
Question: Which institute is known as International money laundering watch dog?
Answer: Financial Action Task Force (FATF)
Question: What do the authors hypothesize due to the source language and the assisting language (English) having different word orders?
Evidence: Consider the task of translating from an extremely low-resource language (source) to a target language. The parallel corpus between the two languages if available may be too small to train a NMT model. Similar to existing works BIBREF3 , BIBREF10 , BIBREF12 , we use transfer learning to overcome data sparsity and train a NMT model between the source and the target languages. Specifically, the NMT model (parent model) is trained on the assisting language and target language pairs. We choose English as the assisting language in all our experiments. In our resource-scarce scenario, we have no parallel corpus for the child task. Hence, at test time, the source language sentence is translated using the parent model after performing a word-by-word translation into the assisting language.
Since the source language and the assisting language (English) have different word order, we hypothesize that it leads to inconsistencies in the contextual representations generated by the encoder for the two languages. In this paper, we propose to pre-order English sentences (assisting language sentences) to match the word-order of the source language and train the parent model on this pre-ordered corpus. In our experiments, we look at scenarios where the assisting language has SVO word order and the source language has SOV word order.
For instance, consider the English sentence Anurag will meet Thakur. One of the pre-ordering rule swaps the position of the noun phrase followed by a transitive verb with the transitive verb. The original and the resulting re-ordered parse tree will be as shown in the Table TABREF5 . Applying this reordering rule to the above sentence Anurag will meet Thakur will yield the reordered sentence Anurag Thakur will meet. Additionally, the Table TABREF5 shows the parse trees for the above sentence with and without pre-ordering.
Pre-ordering should also be beneficial for other word order divergence scenarios (e.g., SOV to SVO), but we leave verification of these additional scenarios for future work.
Since the source language and the assisting language (English) have different word order, we hypothesize that it leads to inconsistencies in the con textual representations generated by the encoder for the two languages.
Answer: The authors hypothesize that it leads to inconsistencies in the con textual representations generated by the encoder for the two languages.
Question: How can I make the paint color purple from primary colors?
Answer: By combining Red and Blue primary colors, you can make purple.
Question: Which items on this list are scientific instruments and which are musical instruments: guitar, microscope, drums, petri dish, piano, trumpet, and bunsen burner.
Answer: The scientific instruments on this list include the microscope, petri dish and bunsen burner, and the musical instruments are the guitar, drums, piano, and trumpet.
Question: give me a list of ways some one can warm up
Answer: - go under the covers
- start a fire 
- drink a hot beverage
- snuggle up with someone else
- take a dip in a hot spring
- do a few jumping jacks
- put more clothes on
- go in a sauna
- take a trip to a tropical destination
- turn on an electric heater
- turn on the car heater
Question: Are the tweets specific to a region?
Evidence: We collect data by using the Twitter API for saved data, available for public use. For our experiments we collect 3200 tweets filtered by keywords like “fire”, “earthquake”, “theft”, “robbery”, “drunk driving”, “drunk driving accident” etc. Later, we manually label tweets with and labels for classification as stage one. Our dataset contains 1313 tweet with positive label and 1887 tweets with a negative label . We create another dataset with the positively labeled tweets and provide them with category labels like “fire”, “accident”, “earthquake” etc.
Answer: No.
Question: What algorithm and embedding dimensions are used to build the task-specific embeddings?
Evidence: We further use as features the embeddings of the claim, of the best-scoring snippet, and of the best-scoring sentence triplet from a Web page. We calculate these embeddings (i) as the average of the embeddings of the words in the text, and also (ii) using LSTM encodings, which we train for the task as part of a deep neural network (NN). We also use a task-specific embedding of the claim together with all the above evidence about it, which comes from the last hidden layer of the NN.
We further use as features the embeddings of the claim, of the best-scoring snippet, and of the best-scoring sentence triplet from a Web page. We calculate these embeddings (i) as the average of the embeddings of the words in the text, and also (ii) using LSTM encodings, which we train for the task as part of a deep neural network (NN). We also use a task-specific embedding of the claim together with all the above evidence about it, which comes from the last hidden layer of the NN.
Answer: The answers are shown as follows:
*  task-specific embedding of the claim together with all the above evidence about it, which comes from the last hidden layer of the NN
Question: What does the FraCaS test suite consist of?
Evidence: The FraCaS test suite is an NLI data set consisting of 346 inference problems. Each problem contains one or more premises followed by one yes/no-question. There is a three way classification: YES, NO or UNK (unknown, see Figure 1 for an example from FraCaS). The FraCaS test suite was later on turned into machine-readable format by Bill McCartney
Expansions of FraCaS include: a) MultiFraCaS, in effect a multilingual FraCaS, and b) JSem, the Japanese counterpart to FraCaS, which expands the original FraCaS in a number of ways.
Even though the FraCaS test suite contains a rather small number of examples (346), it covers a lot of NLI cases and is, at least to some extent, multilingual. It is to some extent precise, even though there are test cases that do not involve a clear answer and thus are dubbed as undefined in Bill MacCartney's XML version. A further drawback of the FraCaS test stuite is that it involves constructed examples, rather than real text.
An UNK example from the FraCaS test suite.
A Scandinavian won the Nobel Prize.
Every Swede is Scandinavian.
Did a Swede win the Nobel prize?
A Swede won the Nobel prize.
UNK [FraCaS 065]
The FraCaS test suite is an NLI data set consisting of 346 inference problems.
Answer: The FraCaS test suite is an NLI data set consisting of 346 inference problems.
Question: Who directed the Game of Thrones season three episode titled "Kissed by Fire"?
Answer: Alex Graves directed "Kissed by Fire." He also directed the season three episode "And Now His Watch Is Ended."
Question: Prince introduced his iconic symbol on the cover of which single?
Answer: 1999.
Question: Who was charged in August 1902, under the Offences against the Person Act 1861 with incitement to murder?
Evidence: In August 1902, he was charged under the Offences against the Person Act 1861 with incitement to murder - during the course of a speech against an eviction - of Major-General Devinish Meares. That December, he was found guilty and sentenced to eight months' imprisonment. After the passing of the Evicted Tenants Act, 1908, some of this holding, but not his house, was returned to him
Answer: Denis Kilbride (September 1848 – 24 October 1924) was an Irish nationalist politician, who as member of the Irish Parliamentary Party represented South Kerry (1887–1895), and North Galway (1895–1900) and South Kildare (1903–1918) as a Member of Parliament (MP) in the House of Commons of the United Kingdom of Great Britain and Ireland.

He was educated at Clongowes Wood. He was evicted, along with other subtenants of the 5th Marquess of Lansdowne, was evicted from his 500-acre (2.0 km2) holding during the Luggacurran evictions, Stradbally, County Laois, in March 1887.

Kilbride's rent was 760 pounds a year, although the holding was valued at only 450. Although he was a large tenant, he and other tenants adopted the Plan of Campaign.

To raise awareness of the evictions, Kilbride travelled with William O'Brien to Canada, where the Marquess of Lansdowne was governor general, and the USA.

In August 1902, he was charged under the Offences against the Person Act 1861 with incitement to murder - during the course of a speech against an eviction - of Major-General Devinish Meares. That December, he was found guilty and sentenced to eight months' imprisonment. After the passing of the Evicted Tenants Act, 1908, some of this holding, but not his house, was returned to him.

He died at his residence in Luggacurran in 1924 aged 76 and was buried in Clopook cemetery.
Question: Given this paragraph on Macquarie University Real Tennis Club, please tell me how many tennis courts the club had.
Evidence: The Macquarie University Real Tennis Club (formerly the Sydney Real Tennis Club) played real tennis at Macquarie University in Sydney, Australia. Its only court closed on 31 December 2005, converted to other athletic uses. However, the university has agreed to provide land for another court as well as A$350,000 toward its construction. The club is working to provide additional funds required to begin construction.
Answer: Based on this paragraph, it appears that the Macquarie University Real Tennis Club had only one tennis court.
Question: what was their baseline comparison?
Evidence: To compare our neural models with the traditional approaches, we experimented with a number of existing models including: Support Vector Machine (SVM), a discriminative max-margin model; Logistic Regression (LR), a discriminative probabilistic model; and Random Forest (RF), an ensemble model of decision trees. We use the implementation from the scikit-learn toolkit BIBREF19 . All algorithms use the default value of their parameters.
To compare our neural models with the traditional approaches, we experimented with a number of existing models including: Support Vector Machine (SVM), a discriminative max-margin model; Logistic Regression (LR), a discriminative probabilistic model; and Random Forest (RF), an ensemble model of decision trees.
Answer: The answers are shown as follows:
* Support Vector Machine (SVM)
* Logistic Regression (LR)
* Random Forest (RF)
Question: Does Bolivia have a wine scene?
Answer: Bolivia and more specifically, Tarija, have a wonderful wine scene that has continued to develop in the shadow of its southern neighbor, Mendoza. The high altitudes and clay soil produce many excellent varietals of grape, of which they are most predominantly known for their, Tannat, a full bodied red wine originating from France and thriving in South America.
Question: Why practicing sport is important ?
Answer: Practicing sport is important for your physical health and mental health. It teaches you to set goals and and how to reach them. You will learn discipline, consistency and regularity. But it's also very important for you physical health because of the endorphins and dopamina it secretes. It regulates your blood pressure level. It will reduce your stress, improve your sleep and you will feel happier.
Question: What are the steps I should take to become a data engineer for absolute beginner?
Answer: 1. Learn about Database systems and how data is store. (Get to know some history too of early Database Management Systems (DBMS))

2. Learn SQL. 

3. Learn tuning and how to write efficient queries

4. Learn Python.

5. Learn a distributed data processing framework like Spark.

6. Do some personal projects.
Question: How many arms does Hapalochlaena lunulata have?
Evidence: The greater blue-ringed octopus (Hapalochlaena lunulata) is one of four species of extremely venomous blue-ringed octopuses belonging to the family Octopodidae. This particular species of blue-ringed octopus is known as one of the most toxic marine animals in the world.
Answer: Hapalochlaena lunulata is an octopus, so it must have eight arms.
Question: What is binary search ?
Evidence: In computer science, binary search, also known as half-interval search, logarithmic search, or binary chop, is a search algorithm that finds the position of a target value within a sorted array. Binary search compares the target value to the middle element of the array. If they are not equal, the half in which the target cannot lie is eliminated and the search continues on the remaining half, again taking the middle element to compare to the target value, and repeating this until the target value is found. If the search ends with the remaining half being empty, the target is not in the array.

The binary search runs in logarithmic time in the worst case, making 

O(log n) comparisons, where 

n is the number of elements in the array. Binary search is faster than linear search except for small arrays. However, the array must be sorted first to apply binary search. There are specialized data structures designed for fast searching, such as hash tables, that can be searched more efficiently than binary search. However, binary search can solve a wider range of problems, such as finding the next-smallest or next-largest element in the array relative to the target even if it is absent from the array.

There are numerous variations of binary search. In particular, fractional cascading speeds up binary searches for the same value in multiple arrays. Fractional cascading efficiently solves several search problems in computational geometry and numerous other fields. Exponential search extends binary search to unbounded lists. The binary search tree and B-tree data structures are based on binary search.
Answer: Binary search is a search algorithm that finds the position of a target value in a sorted array. It eliminates the half in which the target value cannot lie. It searches the value in the other half. This continues by repeating the middle element to compare to the target value until the target value is found. 
Binary search is faster than linear search except for small arrays.
Question: Think of 5 different ways I can cook a chicken breast without a traditional oven or stove.
Answer: Here are 5 ways you could get creative and cook chicken without a stove:
1. Make a small fire and roast the chicken. Be sure to be outdoors!
2. Travel to a location in a desert climate (like Arizona) and place the chicken on the hood of your car on a hot day.
3. Put the chicken in the microwave for a really really long time.
4. Refract the sun through a magnifying glass at the chicken for a very long time.
5. And my personal favorite, bring your chicken to a science lab and roast it over a Bunsen burner!