DataHammer/scimrc huggingface dataset:
Question: How do UK telephone numbers work?
Answer: The UK telephone numbering system has a strange and complicated pattern which is born out of many historical changes and anomalies. Essentially nearly all numbers start with 0 when dialled in the UK. The leading 0 is omitted when calling from overseas and the prefix "+44" is added in its place. The second digit indicates what type of number it is. So called geographic numbers (those associated with an area code) start with 01or 02. Numbers starting with 03 are not associated with any area code but are charged at the same rates as numbers beginning with 01 or 02. Mobile numbers always start with 07. Numbers starting 09 are premium rate numbers which incur high charges for providing additional services.  Numbers starting with 080 are toll free. Other numbers starting with 08 are charged at special rates but not the very high rates for 09 numbers.

Special numbers that do not start with 0 include 999 and 112 for emergencies, 101 for non emergency Police matters, 111 for contacting the National Health Service in a non emergency and directory enquiries services that start with 118.

The history of UK area codes (beginning 01 and 02) dates back to the times when individual telephone exchanges had their own one, two or three character Subscriber Trunk Dialing (STD) codes (e.g. B for Birmingham or AY6 for Aylesbury). in 1966 STD codes were converted to numbers using the number patterns on telephone dials (where 2=ABC, 3 = DEF etc.) so Birmingham became 021, Aylesbury became 0296. 01 was the code allocated to London. Area codes were between 2 and five characters long including the leading zero. Following the area code a local number of between 3 and 7 digits was added for each line to make the complete number either 9 or 10 digits long. Callers within the same area code could dial other lines with the same code by simply dialling the local number omitting the area code. In 1968 area codes beginning 00 were moved to free up 00 for other uses.

By the 1980s a number of factors meant that some areas, especially London, were running out of codes. Various measures were introduced including, in 1990,  the splitting of London into 071 (inner London) and 081 (outer London).

The 80s and 90s also saw the gradual introduction of "non geographic" numbers e.g. the toll free 0800 numbers and a number of patterns for emerging mobile services. Premium rate services were also launched using 0898.

In 1995 on so called "phONEday" a leading 1 was added after the zero. London numbers became either 0171 or 0181, Birmingham 0121, Aylesbury 01296 etc.

This established the pattern we see today allowing for some area codes to move to "02" codes over the next few years. In addition larger cities were allocated new codes beginning 011 e.g. 0113 for Leeds, 0117 for Bristol.

In 2000 the "big number change" saw London codes changed yet again = 0171 became 020 7 and 0181 became 020 8 allowing for new London numbers to be issued starting with 020 3 and 020 4 . Other cities that gained "02" style codes were Southampton/Portsmouth 023 , Coventry 024 and Cardiff 029.  A unified code of 028 was introduced in Northern Ireland.
Question: Identify which instrument is string or percussion: Kebero, Vlier
Answer: Vlier is string, Kebero is percussion.
Question: What text sequences are associated with each vertex?
Evidence: Although these methods have demonstrated performance gains over structure-only network embeddings, the relationship between text sequences for a pair of vertices is accounted for solely by comparing their sentence embeddings. However, as shown in Figure 1 , to assess the similarity between two research papers, a more effective strategy would compare and align (via local-weighting) individual important words (keywords) within a pair of abstracts, while information from other words (e.g., stop words) that tend to be less relevant can be effectively ignored (down-weighted). This alignment mechanism is difficult to accomplish in models where text sequences are first embedded into a common space and then compared in pairs BIBREF14 , BIBREF15 , BIBREF16 , BIBREF17 , BIBREF18 .
We propose to learn a semantic-aware Network Embedding (NE) that incorporates word-level alignment features abstracted from text sequences associated with vertex pairs. Given a pair of sentences, our model first aligns each word within one sentence with keywords from the other sentence (adaptively up-weighted via an attention mechanism), producing a set of fine-grained matching vectors. These features are then accumulated via a simple but efficient aggregation function, obtaining the final representation for the sentence. As a result, the word-by-word alignment features (as illustrated in Figure 1 ) are explicitly and effectively captured by our model. Further, the learned network embeddings under our framework are adaptive to the specific (local) vertices that are considered, and thus are context-aware and especially suitable for downstream tasks, such as link prediction. Moreover, since the word-by-word matching procedure introduced here is highly parallelizable and does not require any complex encoding networks, such as Long Short-Term Memory (LSTM) or Convolutional Neural Networks (CNNs), our framework requires significantly less time for training, which is attractive for large-scale network applications.
However, as shown in Figure 1 , to assess the similarity between two research papers, a more effective strategy would compare and align (via local-weighting) individual important words (keywords) within a pair of abstracts, while information from other words (e.g., stop words) that tend to be less relevant can be effectively ignored (down-weighted). 
We propose to learn a semantic-aware Network Embedding (NE) that incorporates word-level alignment features abstracted from text sequences associated with vertex pairs. Given a pair of sentences, our model first aligns each word within one sentence with keywords from the other sentence (adaptively up-weighted via an attention mechanism), producing a set of fine-grained matching vectors
Answer: The answers are shown as follows:
* abstracts
* sentences
Question: Best singer in the World  in Hindi
Answer: Asha Bhosle and Kishore Kumar
Question: What are the 4 Commercial prompts?
Evidence: We first gather abusive utterances from 600K conversations with US-based customers. We search for relevant utterances by simple keyword spotting and find that about 5% of the corpus includes abuse, with mostly sexually explicit utterances. Previous research reports even higher levels of abuse between 11% BIBREF2 and 30% BIBREF6. Since we are not allowed to directly quote from our corpus in order to protect customer rights, we summarise the data to a total of 109 “prototypical" utterances - substantially extending the previous dataset of 35 utterances from Amanda:EthicsNLP2018 - and categorise these utterances based on the Linguistic Society's definition of sexual harassment BIBREF7:
[noitemsep]
Gender and Sexuality, e.g. “Are you gay?”, “How do you have sex?”
Sexualised Comments, e.g. “I love watching porn.”, “I'm horny.”
Sexualised Insults, e.g. “Stupid bitch.”, “Whore”
Sexual Requests and Demands, e.g. “Will you have sex with me?”, “Talk dirty to me.”
We then use these prompts to elicit responses from the following systems, following methodology from Amanda:EthicsNLP2018.
[leftmargin=5mm, noitemsep]
4 Commercial: Amazon Alexa, Apple Siri, Google Home, Microsoft's Cortana.
4 Non-commercial rule-based: E.L.I.Z.A. BIBREF8, Parry BIBREF9, A.L.I.C.E. BIBREF10, Alley BIBREF11.
4 Data-driven approaches:
Cleverbot BIBREF12;
NeuralConvo BIBREF13, a re-implementation of BIBREF14;
an implementation of BIBREF15's Information Retrieval approach;
a vanilla Seq2Seq model trained on clean Reddit data BIBREF1.
Negative Baselines: We also compile responses by adult chatbots: Sophia69 BIBREF16, Laurel Sweet BIBREF17, Captain Howdy BIBREF18, Annabelle Lee BIBREF19, Dr Love BIBREF20.
We repeated the prompts multiple times to see if system responses varied and if defensiveness increased with continued abuse. If this was the case, we included all responses in the study. Following this methodology, we collected a total of 2441 system replies in July-August 2018 - 3.5 times more data than Amanda:EthicsNLP2018 - which 2 expert annotators manually annotated according to the categories in Table TABREF14 ($\kappa =0.66$).
4 Commercial: Amazon Alexa, Apple Siri, Google Home, Microsoft’s Cortana.
Answer: Amazon Alexa, Apple Siri, Google Home, Microsoft’s Cortana.
Question: Which are the top 3 states of India that account for receiving the maximum number of interstate emigrants?
Evidence: The first population census in India was conducted in 1873. Since then the a decennial census has been conducted in 1881, 1891, 1901, 1911, 1921, 1931, and 1941 by the Government. Since India's independence in 1947, a census has been carried out every 10 years by the Indian Government, starting from 1951. The census in India is carried out by the Office of the Registrar General and Census Commissioner under the Ministry of Home Affairs, and is one of the largest administrative tasks conducted by a federal government.

Latest population figures are based on data from the 2011 census of India. During the decade of 2001–2011, India's annual population rising rate has slowed down from 2.15 to 1.76. Based on decennial census data, Dadra and Nagar Haveli shows the highest growth rate of 55.5 percent. It is followed by Daman and Diu (53.5 percent), Meghalaya (27.8 percent) and Arunachal Pradesh (25.9 percent). Nagaland recorded the lowest growth rate of -0.5 percent.

India has 641,000 inhabited villages and 72.2 percent of the total population reside in these rural areas. Of them, 145,000 villages have a population size of 500–999 persons; 130,000 villages have a population size of 1000–1999 and 128,000 villages have a population size of 200–499. There are 3,961 villages that have a population of 10,000 persons or more. India's 27.8 percent urban population lives in more than 5,100 towns and over 380 urban agglomerations. In the decade of 1991–2001, migration to major cities caused a rapid increase in urban population. On the basis of net migrants by last residence during the past decade, Maharashtra had the most immigration with 2.3 million, followed by the National Capital Territory of Delhi (1.7 million), Gujarat (0.68 million) and Haryana (0.67 million). Uttar Pradesh (−2.6 million) and Bihar (−1.7 million) topped the list for interstate emigration. The four states of Uttar Pradesh, Maharashtra, Bihar, West Bengal and account for almost half (48.89 percent) of the total Indian population.
Answer: Maharashtra, National Capital of Delhi and Gujarat
Question: Given this paragraph about the First Treaty that was signed after the Russo-Japanese War, was there a secret component?
Evidence: After the Russo-Japanese War, the First Treaty was signed on 30 July 1907 by Motono Ichirō, the Japanese Ambassador in Moscow, and Alexander Izvolsky, the Foreign Minister of Russian. The treaty was divided into two parts: one is open agreement, which respected the treaties concluded between the two countries and China, respected China's independence, promoted open doors, and achieved equal opportunities and another is secret agreement, which defined the scope of Japan's interests in Southern Manchuria and Russia's interests in Northern Manchuria and Japan recognized Russia's interests in Outer Mongolia, and Russia recognized Japan's interests in the Korean Peninsula.
Answer: Yes. The second part of the First Treaty contained a secret agreement which defined the political scope of each party's interest.
Question: What is a mediterranean diet?
Answer: The mediterranean diet consists of traditional foods from countries bordering the mediterranean sea, such as Greece, France, and Italy. The diet typically contains fruits, vegetables, whole grains, lentils, nuts, and seeds. Extra-virgin olive oil is a typical source of healthy fats. The diet does not contain heavily processed foods, products with added sugar, or large amounts of unhealthy fats as found in butter, red meat, and cheese.
Question: Give me a list of great computer games
Answer: Sure, I will list a few great computer games, but be aware that there are many great computer games way more than what I can list here. 

- Elden Ring
- World of Warcraft
- Hogwarts Legacy
- Hearthstone
- Minecraft
- Civilization
- Dota
- Cities: Skylines
Question: Why is it important to be passionate about one's choice of career?
Answer: Passion is infectious. When you show passion in what you do, it rubs off on others around you, and brings out their best. If you like what you do, it is easy to get up every morning and go to work. Conversely, if you intentionally pick your career mostly for the money, it gets old pretty soon. Finally, if you do not love what you do, it is unlikely that you will stick to it for long. Burn out rates are high in high stress careers.
Question: It is not clear what is evaluated in Section 5, is it the training set or test set?
Evidence: We test our model on 3 image datasets for image synthesis. (i) CIFAR-10 (Krizhevsky & Hinton,2009) is a dataset containing 50k training images and 10k testing images in 10 classes; (ii) SVHN (Netzer et al., 2011) is a dataset containing over 70k training images and over 20k testing images of house numbers; (iii) CelebA (Liu et al., 2015) is a celebrity facial dataset containing over 200k imagess.
Answer: We calculate the FID score using the samples we generate from the model with the training set data. While in the image reconstruction task, we carry our experments on the test set of CIFAR-10 dataset. For the inpainting and interpolation experiments, we use the CelebA dataset. Given this dataset usually doesn't have a training and testing slipt. We train the model on all the data and thus the inpainting and interpolation are done on training set. We have also modified our paper to make this more clear.
Question: Who called Timothy Leary a brave neuronaut?
Evidence: Timothy Francis Leary (October 22, 1920 – May 31, 1996) was an American psychologist and author known for his strong advocacy of psychedelic drugs. Evaluations of Leary are polarized, ranging from bold oracle to publicity hound. He was "a hero of American consciousness", according to Allen Ginsberg, and Tom Robbins called him a "brave neuronaut"
Answer: Tom Robbins called Timothy Leary a "brave neuronaut".
Question: Extract the year that the Volvo XC40 was released.
Evidence: The Volvo XC40 is a subcompact luxury crossover SUV manufactured by Volvo Cars. It was unveiled on 21 September 2017 as the smallest SUV model from Volvo, below the XC60. Orders started in September of 2017, and manufacturing began in November 2017. It was introduced with conventional petrol and diesel engines, with a plug-in hybrid model being introduced in 2019, and a battery electric vehicle model was released in 2020 as the XC40 Recharge. A version of the battery electric model with a sloping rear roof was released in 2021 as the C40 Recharge.
Answer: The XC40 was released in the year 2017.
Question: What is photosynthesis?
Answer: Photosynthesis is a process in plants that converts energy from light into chemical energy.
Question: What makes us happy ?
Answer: While there is no one definition of happiness, following traits are common across happy people:
1) Strong social network
2) Financial stability
3) High job satisfaction
4) Strong family connections
5) Participate in extracurricular activities
Question: Where is located the Roberson Museum and Science Center?
Evidence: The Roberson Museum and Science Center is located in Binghamton, New York. The museum's exhibits focus on art, local history, science and natural history.
Answer: The Roberson Museum and Science Center is located in Binghamton, New York. The museum's exhibits focus on art, local history, science and natural history.

The centerpiece of the museum is the 1904 Roberson Mansion, which was designed by local architect C. Edward Vosbury. More contemporary additions to the mansion were added in the 1960s and 1980s, which expanded the exhibit space, included a planetarium, added offices, and upgraded the vaults and collections preparation space.

The museum features changing exhibits and a large model train layout that depicts regional landscapes in the 1950s. The museum hosts annual special events, including decorating the Roberson Mansion for the Christmas holidays, a food and wine festival, Halloween activities, science fiction conventions, a model train and doll fair, and more.
Question: What kind of model is their speech recognition system?
Evidence: Our speech recognition system, builds on the recently proposed Listen, Attend and Spell network BIBREF12 . It is an attention-based seq2seq model that is able to directly transcribe an audio recording INLINEFORM0 into a space-delimited sequence of characters INLINEFORM1 . Similarly to other seq2seq neural networks, it uses an encoder-decoder architecture composed of three parts: a listener module tasked with acoustic modeling, a speller module tasked with emitting characters and an attention module serving as the intermediary between the speller and the listener: DISPLAYFORM0 
It is an attention-based seq2seq model that is able to directly transcribe an audio recording INLINEFORM0 into a space-delimited sequence of characters INLINEFORM1 .
Answer: An attention-based seq2seq model.
Question: What is celiac disease?
Answer: Celiac disease is an autoimmune disease that is hereditary, not to be confused with gluten intolerance. Celiac disease is an immune response to consuming gluten, a protein found in barley, rye, and wheat, which impacts nutrient absorption and immunity when consumed.
Question: Which is a species of fish? Turbot or Turbo
Answer: Turbot
Question: Why Paris is know as the city of light ?
Answer: This is more a marketing conception of Paris, some historians think that this name came from the time where Philippe Lebon installed gas lighting on city monuments, covered passages and streets. Since then, more than 56000 street lights  make Paris the city of light
Question: What are several ways to keep a toddler busy?
Answer: There are many fun ways to keep a toddler busy. First, you could find some blocks or large legos and build a tower. Then, you could ask the toddler to glue sticks to a piece of paper. Toddlers love water, so you could put water in a pot and give the toddler some cups to play with the water. You could take a walk and play the game "I spy." While you are walking, ask the toddler to collect leaves, sticks and rocks. You could also sing any song that comes to mind, as many toddlers enjoy singing.
Question: What is the Maareech Advanced Torpedo Defence System (ATDS)?
Evidence: Maareech Advanced Torpedo Defence System (ATDS) is a torpedo detection and countermeasure system used by the Indian Navy. The system offers a complete solution to detect and locate an incoming torpedo and to apply countermeasures to protect naval platform against torpedo attack. It was developed as a joint project of the Naval Physical and Oceanographic Laboratory (NPOL), Kochi and the Naval Science and Technological Laboratory (NSTL), Visakhapatnam. Bharat Electronics is manufacturing it India.
Answer: The Maareech Advanced Torpedo Defence System (ATDS is a torpedo detection and countermeasure system used by the Indian Navy.
Question: Does the authors' LDR obtain competitive results compared with the use of distributed representations?
Evidence: In Table 6 we show the results obtained by the described representations employing the Multiclass Classifier. As can be appreciated, the proposed low dimensionality representation improves more than 35% the results obtained with the state-of-the-art representations. BOW obtains slightly better results than character 4-grams, and both of them improve significantly the ones obtained with tf-idf 2-grams. Instead of selecting the most frequent $n$ -grams, our approach takes advantage from the whole vocabulary and assigns higher weights to the most discriminative words for the different language varieties as shown in Equation 10 .
 We highlight that our LDR obtains competitive results compared with the use of distributed representations. Concretely, there is no significant difference among them (Skip-gram $z_{0.05} = 0,5457 < 1,960$ and SenVec $z_{0.05} = 0,7095 < 1,960$ ). In addition, our proposal reduces considerably the dimensionality of one order of magnitude as shown in Table 6 .
We highlight that our LDR obtains competitive results compared with the use of distributed representations.
Answer: Yes, it does.
Question: Identify which instrument is string or percussion: Boobam, Orutu
Answer: Boobam is percussion, Orutu is string.
Question: From the article, tell me why the trail beneath the Landscape Arch has been closed.
Evidence: Landscape Arch is a natural arch in Arches National Park, Utah, United States. It is among the longest natural rock arches in the world. The arch is among many in the Devils Garden area in the north of the park. Landscape Arch was named by Frank Beckwith who explored the area in the winter of 1933–1934 as the leader of an Arches National Monument scientific expedition. The arch can be reached by a 0.8 mi (1.3 km) graded gravel trail.

The Natural Arch and Bridge Society (NABS) considers Landscape Arch the fifth longest natural arch in the world, after four arches in China. In 2004, the span of Landscape Arch was measured at 290.1 ft (88.4 m), ±0.8 ft (0.24 m), with a height of 77.5 ft (23.6 m). NABS measured the span of the slightly shorter Kolob Arch in Zion National Park at 287 ft (87 m) in 2006.

The most recent recorded rockfall events occurred in the 1990s when one large slab fell in 1991 and then two additional large rockfalls occurred in 1995. Since the rockfalls, the trail beneath the arch has been closed.
Answer: The trail beneath the Landscape Arch has been closed because of rockfall events. The most recent recorded rockfall events occurred in the 1990s when one large slab fell in 1991 and then two additional large rockfalls occurred in 1995.
Question: Is the semantic hierarchy representation used for any task?
Evidence: Moreover, most current Open IE approaches output only a loose arrangement of extracted tuples that are hard to interpret as they ignore the context under which a proposition is complete and correct and thus lack the expressiveness needed for a proper interpretation of complex assertions BIBREF8. As illustrated in Figure FIGREF9, with the help of the semantic hierarchy generated by our discourse-aware sentence splitting approach the output of Open IE systems can be easily enriched with contextual information that allows to restore the semantic relationship between a set of propositions and, hence, preserve their interpretability in downstream tasks.
As illustrated in Figure FIGREF9, with the help of the semantic hierarchy generated by our discourse-aware sentence splitting approach the output of Open IE systems can be easily enriched with contextual information that allows to restore the semantic relationship between a set of propositions and, hence, preserve their interpretability in downstream tasks.
Answer: Yes.