DataHammer/scimrc huggingface dataset:
Question: List down some points about life of cricketer Peggy Antonio from the given passage
Evidence: Peggy Antonio (2 June 1917 – 11 January 2002, Melbourne, Australia) was an Australian women's Test cricketer, known as the "Girl Grimmett".

Antonio was raised in Port Melbourne, Victoria, a working class suburb of Melbourne. Her father was a Chilean docker of French and Spanish descent who died when she was 15 months. With the encouragement of her uncle she learnt her cricket from the boys in her neighbourhood streets. As a young girl during the Great Depression, she was lucky enough to find work at a shoe factory in the industrial suburb of Collingwood. The factory was home to a women's cricket team where Antonio came to the attention of Eddie Conlon, a club cricketer with an encyclopaedic knowledge of the game. With the assistance of Conlon, Antonio developed a rare mix of leg spin and off spin, including a top spinner and a wrong'un.
Answer: 1. Peggy Antonio, also referred to as the "Girl Grimmett," played women's Test cricket for Australia and died on January 11, 2002, in Melbourne, Australia.
2. Antonio grew up in the working-class Melbourne district of Port Melbourne, Victoria.
3. When she was 15 months old, her father, a Chilean docker of French and Spanish ancestry, passed away.
4. With her uncle's encouragement, she picked up cricket from the guys on the streets of her area.
5. She was fortunate enough to work at a shoe factory in the Collingwood industrial area during the Great Depression as a young child.
6. Eddie Conlon, a club cricketer with encyclopaedic knowledge of the game, saw Antonio when he was playing for the women's cricket team at the factory.
7. With Conlon's help, Antonio created an uncommon combination of leg spin and off spin, including a top spinner and a wrong'un.
Question: What technique does the author use?
Evidence: Informal speech is different from formal speech, especially in Vietnamese due to many conjunctive words in this language. Building an ASR model to handle such kind of speech is particularly difficult due to the lack of training data and also cost for data collection. There are two components of an ASR system that contribute the most to the accuracy of it, an acoustic model and a language model. While collecting data for acoustic model is time-consuming and costly, language model data is much easier to collect.
The language model training for the Automatic Speech Recognition (ASR) system usually based on corpus crawled on formal text, so that some conjunctive words which often used in conversation will be missed out, leading to the system is getting biased to writing-style speech.
In this paper, we present our attempt to mitigate the problems using a large scale data set and a language model combination technique that only require a small amount of conversation data but can still handle very well conversation speech.
In this paper, we present our attempt to mitigate the problems using a large scale data set and a language model combination technique that only require a small amount of conversation data but can still handle very well conversation speech.
Answer: A language model combination technique.
Question: What are the languages they consider in this paper?
Evidence: To test this hypothesis we first trained UG-WGAN in English, Chinese and German following the procedure described in Section "UG-WGAN" . The embedding size of the table was 300 and the internal LSTM hidden size was 512. A dropout rate of $0.1$ was used and trained with the ADAM optimization method BIBREF23 . Since we are interested in the zero-shot capabilities of our representation, we trained our sentiment analysis model only on the english IMDB Large Movie Review dataset and tested it on the chinese ChnSentiCorp dataset and german SB-10K BIBREF24 , BIBREF25 . We binarize the label's for all the datasets.
For this experiment we trained UG-WGAN on the English and Russian language following the procedure described in Section "UG-WGAN" . We kept the hyper-parameters equivalent to the Sentiment Analysis experiment. All of the NLI model tested were run over the fixed UG embeddings. We trained two different models from literature, Densely-Connected Recurrent and Co-Attentive Network by BIBREF30 and Multiway Attention Network by BIBREF31 . Please refer to this papers for further implementation details.
One way to measure universality is by studying perplexity of our multi-lingual language model as we increase the number of languages. To do so we trained 6 UG-WGAN models on the following languages: English, Russian, Arabic, Chinese, German, Spanish, French. We maintain the same procedure as described above. The hidden size of the language model was increased to 1024 with 16K BPE tokens being used. The first model was trained on English Russian, second was trained on English Russian Arabic and so on. For arabic we still trained from left to right even though naturally the language is read from right to left. We report the results in Figure 5 . As the number of languages increases the gap between a UG-WGAN without any distribution matching and one with diminishes. This implies that the efficiency and representative power of UG-WGAN grows as we increase the number of languages it has to model.
To test this hypothesis we first trained UG-WGAN in English, Chinese and German following the procedure described in Section "UG-WGAN" .
For this experiment we trained UG-WGAN on the English and Russian language following the procedure described in Section "UG-WGAN" . 
To do so we trained 6 UG-WGAN models on the following languages: English, Russian, Arabic, Chinese, German, Spanish, French.
Answer: The languages considered were English, Chinese, German, Russian, Arabic, Spanish, French
Question: Extract the stock ticker from the following text
Evidence: Pfizer (2021).svg
Corporate logo since 2021
Pfizer World Headquarters Entrance.jpg
Headquarters on 42nd Street in Midtown Manhattan
Type	Public
Traded as	
NYSE: PFE
S&P 100 component
S&P 500 component
Industry	
Pharmaceutical
Biotechnology
Founded	1849; 174 years ago in New York City
Founders	
Charles Pfizer
Charles F. Erhart
Headquarters	New York City, U.S.
Area served	Worldwide
Key people	Albert Bourla (CEO)
Products	
Pharmaceutical drugsvaccines
Revenue	Increase US$100.3 billion (2022)
Operating income	Increase US$31.40 billion (2022)
Net income	Increase US$31.37 billion (2022)
Total assets	Increase US$197.2 billion (2022)
Total equity	Increase US$95.66 billion (2022)
Number of employees	c. 83,000 (2022)
Answer: NYSE: PFE
Question: Which models do they try out?
Evidence: FLOAT SELECTED: Table 4: Performance of various methods and human.
FLOAT SELECTED: Table 4: Performance of various methods and human.
Answer: DocQA, SAN, QANet, ASReader, LM, Random Guess
Question: What is the use of a vaccine?
Evidence: A vaccine is a biological preparation that provides active acquired immunity to a particular infectious or malignant disease. The safety and effectiveness of vaccines has been widely studied and verified. A vaccine typically contains an agent that resembles a disease-causing microorganism and is often made from weakened or killed forms of the microbe, its toxins, or one of its surface proteins. The agent stimulates the body's immune system to recognize the agent as a threat, destroy it, and to further recognize and destroy any of the microorganisms associated with that agent that it may encounter in the future.
Answer: Vaccines can be used to provide immunity to a specific disease or infection. It works by stimulating the body's immune system to be able to identify and destroy threat agents.
Question: Describe a situation in which scraping data from the web may be justified. Illustrate this situation with a specific example.
Answer: I envisioned a business that tracks all the B2B digital partnerships (data connectors between apps). The B2B partnership data can be easily monetized with ads and can be a data source for content-generation activities like blogs, interactive charts, etc. An example of B2B partnership data is an app store or digital marketplace. (Example - https://ecosystem.hubspot.com/marketplace/apps/). 

HubSpot ecosystem has B2B partnerships with 600+ companies. A rich data set that tracks B2B partnership data must track thousands of companies' App Store or marketplace. For example, the company's marketplace data connectors include the HubSpot ecosystem, Salesforce app exchange, Google Cloud marketplace, Azure, and Dropbox connectors. The B2B data connectors for all the companies must be scrapped from the company's website and are not available via API or other methods.
Question: How would you describe the taste of coffee?
Answer: A hot coffee has an essence of oats, earth, and a bitter chocolate or cacao. Commonly served with some form dairy to cut through the natural bitter taste, and to add additional sweetness. When iced, coffee can transform into a refreshing beverage that has more of a spring morning tone to the aftertaste.
Question: What are microservices?
Answer: Microservices are an architectural and organizational approach to software development where software is composed of small independent services that communicate over well-defined APIs. These services are owned by small, self-contained teams.
Question: What is the mascot of Stanford University?
Answer: The mascot of Stanford is a redwood tree.
Question: What is a laser and who created it?
Evidence: A laser is a device that emits light through a process of optical amplification based on the stimulated emission of electromagnetic radiation. The word laser is an anacronym that originated as an acronym for light amplification by stimulated emission of radiation The first laser was built in 1960 by Theodore Maiman at Hughes Research Laboratories, based on theoretical work by Charles H. Townes and Arthur Leonard Schawlow.

A laser differs from other sources of light in that it emits light that is coherent. Spatial coherence allows a laser to be focused to a tight spot, enabling applications such as laser cutting and lithography. Spatial coherence also allows a laser beam to stay narrow over great distances (collimation), enabling applications such as laser pointers and lidar (light detection and ranging). Lasers can also have high temporal coherence, which allows them to emit light with a very narrow spectrum. Alternatively, temporal coherence can be used to produce ultrashort pulses of light with a broad spectrum but durations as short as a femtosecond.

Lasers are used in optical disc drives, laser printers, barcode scanners, DNA sequencing instruments, fiber-optic, and free-space optical communication, semiconducting chip manufacturing (photolithography), laser surgery and skin treatments, cutting and welding materials, military and law enforcement devices for marking targets and measuring range and speed, and in laser lighting displays for entertainment. Semiconductor lasers in the blue to near-UV have also been used in place of light-emitting diodes (LEDs) to excite fluorescence as a white light source. This permits a much smaller emitting area due to the much greater radiance of a laser and avoids the droop suffered by LEDs; such devices are already used in some car headlamps.
Answer: A laser is a device that emits light from an electromagnetic radiation source.  The first laser was built in 1960 by Theodore Maiman at Hughes Research Laboratories, based on theoretical work by Charles H. Townes and Arthur Leonard Schawlow.

Lasers emit a certain type of light. Light that is coherent. Coherence can be measured spatially or temporally. Spacial coherence allows laser beams to stay narrow over great distances. Temporal coherence can be used to produce ultrashort pules of light. 

Some example of the uses of lasers are optical disc drives, laser printers, barcode scanners, fiber optics and photolithography
Question: How many types of serves exist in tennis?
Evidence: A serve (or, more formally, a service) in tennis is a shot to begin the point. The most common serve is used is an overhead serve. It is initiated by tossing the ball into the air over the server's head and hitting it when the arm is fully stretched out (usually near the apex of its trajectory) into the diagonally opposite service box without touching the net. The server may employ different types of serve: a flat, a top-spin, an American twist (or kick), or a slice serve. A severely sliced serve is sometimes called a sidespin. Some servers are content to use the serve simply to initiate the point; advanced players often try to hit a winning shot with their serve. A winning serve that is not touched by the opponent is called an ace.
Answer: There are different serve types in tennis. Overhead serve, flat serve, top-spin serve, kick serve and slice serve are some of the serve types.
Question: What is the difference between a bass guitar and a normal guitar?`
Answer: A bass guitar typically has four strings which are tuned to G, D, A and E in the standard tuning. A standard guitar, on the other hand, has six strings which are tuned to E, B, G, D, A and E in the standard tuning.
Question: Write about the potential ethical concerns of de-identification techniques.
Answer: One of the ethical issues associated with the technique of suppression is the further underrepresentation of historically underrepresented groups. For example, within the MOOC dataset there exists only one row affiliated with a user from Antartica (continent). Similarly, the following countries have also appeared once or twice only in the entire dataset: San Marino, Falkland Islands, and Brunei. Geographically underrepresented, these pieces of information would get entirely eliminated under the suppression technique. This presents an ethical paradox: on one hand, we wish to preserve k-anonymity and protect the privacy of users from underrepresented regions; on the other hand, to reach that goal we would have to erase their existence in the dataset and further reinforce the pre-existing underrepresentation. Another example would be the column of the year of birth. The MOOCs user population are overrepresented by young people, whereas users over 80 years old only take a proportion less than 1% in the entire dataset. In particular, if we were to use the suppression technique to achieve k-anonymity, almost every piece of information associated with users over 80 years old would have to be discarded. Again, the elderly have been historically underrepresented in the industry of education, yet by using suppression, we protect their privacy at the expense of representation.

This loss of representation as a result of suppression is detrimental at multiple aspects and therefore deserves attention. As the MOOCs platform is deprived of relevant information on these users, the company will lose sight of the potential demand that these underrepresented groups have for online education, thereby failing to reach them through marketing and advertisement. Besides straining the platform’s user base and profitability, this would worsen the situation that the underrepresented groups have limited resources to online education. Moreover, inferences on the suppressed dataset could reinforce the societal bias that certain groups of people are not open to education – such as the elderly – whereas the reality is simply that we erase the information on the elderly who actively engage in online education platforms. As a result, the elderly could feel themselves further distanced from the mainstream media and technology. Therefore, using suppression alone to achieve k-anonymity within a dataset, while effective, could be complicated by the ethical issue of underrepresentation.
Question: Given this paragraph about Bichon Frisé,  where did this dog breed originate?
Evidence: The Bichon Frisé is often depicted as a French dog. Although the Bichon breed type are originally Spanish, used as sailing dogs, also as herding dogs sometimes, the French developed them into a gentle lap-dog variety. The Bichon type arose from the water dogs, and is descended from the poodle-type dogs and either the Barbet or one of the water spaniel class of breeds.
Answer: The Bichon breed type are originally Spanish. The French developed them into a lap-dog variety, and thus the Bichon Frisé is often depicted as a French dog.
Question: Identify which animal is domesticated or wild: Donkey, Leopard ca
Answer: Leopard cat is wild, Donkey is domesticated
Question: Identify which of the following airlines are now defunct: Eastern Air Lines, Alaska Airlines, Virgin America Airlines, Virgin Atlantic Airlines, Pan American World Airways, Tower Air, Braniff International Airways, jetBlue, Spirit Airlines, Flybe
Answer: Eastern Air Lines, Virgin America Airlines, Pan American World Airways, Tower Air, Braniff International Airways, Flybe
Question: Tell me which one of these companies is a popular manufacturer of golf clubs: Ping, Cobra, Nike, Taylormade
Answer: Ping, Cobra and Taylormade are all well known manufacturers of golf clubs and have been for decades. Nike stopped manufacturing golf clubs in 2016 but does continue to market golf clothing and similar accessories.
Question: How is the annotation performed?
Evidence: The annotation was performed using WebAnno BIBREF7, a web-based tool for linguistic annotation. The annotators could choose between a pre-annotated version or a blank version of each text. The pre-annotated versions contained suggested entity spans based on string matches from lists of conditions and findings synonym lists. Their quality varied widely throughout the corpus. The blank version was preferred by the annotators. We distribute the corpus in BioC JSON format. BioC was chosen as it allows us to capture the complexities of the annotations in the biomedical domain. It represented each documents properties ranging from full text, individual passages/sentences along with captured annotations and relationships in an organized manner. BioC is based on character offsets of annotations and allows the stacking of different layers.
The annotation was performed using WebAnno[ https://webanno.github.io/webanno/, 08/04/2019.] (Eckart de Castilho et al., 2016), a web-based tool for linguistic annotation.
Answer: The annotation was performed using WebAnno(Eckart de Castilho et al., 2016), a web-based tool for linguistic annotation.
Question: Give me a list of horror/thriller books to read
Answer: The books of Blood by Clive Barker
A Lush and Seething Hell by John Hornor Jacobs
The Method by James Patterson
Dracula by Bram Stoker
Tender is the Flesh by Agustina Bazrerrica
Salem's Lot by Stephen King
Question: From the passage provided, extract the number of casualties by nation during World War II
Evidence: According to Russian government figures, USSR losses within postwar borders now stand at 26.6 million, including 8 to 9 million due to famine and disease. In August 2009 the Polish Institute of National Remembrance (IPN) researchers estimated Poland's dead at between 5.6 and 5.8 million. Historian Rüdiger Overmans of the Military History Research Office (Germany) published a study in 2000 that estimated the German military dead and missing at 5.3 million, including 900,000 men conscripted from outside of Germany's 1937 borders, in Austria, and in east-central Europe. The Red Army claimed responsibility for the majority of Wehrmacht casualties during World War II. The People's Republic of China puts its war dead at 20 million, while the Japanese government puts its casualties due to the war at 3.1 million.
Answer: USSR - 26.6 million
Poland - 5.8 million
Germany - 5.3 million
China - 20 million
Japan - 3.1 million
Question: Who is the current prime minister of India?
Answer: Shri Narendra Modi is the current prime minister of India.
Question: What is Wikidata?
Evidence: Named-entity recognition (NER) is the task of tagging relevant entities such as person, location and organization in unstructured text. Modern NER has been dominated by neural models BIBREF0, BIBREF1 combined with contextual embeddings from language models (LMs) BIBREF2, BIBREF3, BIBREF4. The LMs are pre-trained on large amounts of unlabeled text which allows the NER model to use the syntactic and semantic information captured by the LM embeddings. On the popular benchmark datasets CoNLL-03 BIBREF5 and Ontonotes 5 BIBREF6, neural models with LMs achieved state-of-the-art results without gazetteers features, unlike earlier approaches that heavily relied on them BIBREF7. Gazetteers are lists that contain entities such as cities, countries, and person names. The gazetteers are matched against unstructured text to provide additional features to the model. Data for building gazetteers is available for multiple language from structured data resources such as Wikipedia, DBpedia BIBREF8 and Wikidata BIBREF9.
In this paper, we propose GazSelfAttn, a novel gazetteer embedding approach that uses self-attention and match span encoding to build enhanced gazetteer representation. GazSelfAttn embeddings are concatenated with the input to a LSTM BIBREF10 or CNN BIBREF11 sequence layer and are trained end-to-end with the model. In addition, we show how to extract general gazetteers from the Wikidata, a structured knowledge-base which is part of the Wikipedia project.
Our contributions are the following:
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We propose novel gazetteer embeddings that use self-attention combined with match span encoding.
We enhance gazetteer matching with multi-token and single-token matches in the same representation.
We demonstrate how to use Wikidata with entity popularity filtering as a resource for building gazetteers.
GazSelfAttn evaluations on CoNLL-03 and Ontonotes 5 datasets show F$_1$ score improvement over baseline model from 92.34 to 92.86 and from 89.11 to 89.32 respectively. Moreover, we perform ablation experiments to study the contribution of the different model components.
In addition, we show how to extract general gazetteers from the Wikidata, a structured knowledge-base which is part of the Wikipedia project.
Answer: A structured knowledge-base which is part of the Wikipedia project.
Question: Given a reference text about Pampaneira, tell me how many people live there, where it's located, and its elevation above sea level.
Evidence: Pampaneira is a village located in the province of Granada, Spain. According to the 2005 census (INE), the village has a population of 355 inhabitants.

It is one of three mountain villages of the Barranco de Poqueira in the Alpujarras region. The other two villages, Bubión and Capileira, are located higher in the Poqueira gorge.

The Poqueira gorge starts below the mountain peak of Mulhacén, where the river Poqueira rises. There are many opportunities for hiking in the area. Guided walks are arranged by the local tourist offices which also sell mountain hiking equipment. Other companies can plan self-guided treks through the area. The nearest major town is Órgiva. One of the highest all year-round lived-in mountain village in Spain, Trevélez is located nearby in the mountains to the east of the three villages.

Accommodation is available in all of the three villages but Capileira has the biggest range of facilities.

At the north side opens the Sierra Nevada (Spain) range with one of the highest peaks in Spain ; Mulhacén and Alcazaba (Sierra Nevada).

The village is located at about 1060 metres above sea level.

There are many craft shops selling ceramics, leather and clothes. Also on offer are the locally produced specialities of cheese and ham.

During the winter the Sierra Nevada and the Alpujarra mountains get covered in snow but the villages are rarely affected by snow for more than a few days a time.

There are bus connections running every day from the town of Granada, Spain.
Answer: Pampaneira is located in the province of Granada, Spain and is 1060 metres above sea level. 355 people live in Pampaneira according to the 2005 census.