DataHammer/scimrc huggingface dataset:
Question: Given a reference text about Hanlon's razor, when did the adage become well-known?
Evidence: Hanlon's razor is an adage or rule of thumb that states, "Never attribute to malice that which is adequately explained by stupidity." Known in several other forms, it is a philosophical razor that suggests a way of eliminating unlikely explanations for human behavior. It is probably named after Robert J. Hanlon, who submitted the statement to Murphy's Law Book Two (1980). Similar statements have been recorded since at least the 18th century.

Origin
A similar quotation appears in Robert A. Heinlein's novella Logic of Empire (1941). The character "Doc" in Heinlein's story described the "devil theory" fallacy, explaining, "You have attributed conditions to villainy that simply result from stupidity."

The quotation as such was a submission credited in print to Robert J. Hanlon of Scranton, Pennsylvania, for a compilation of various jokes related to Murphy's law that were published in Arthur Bloch's Murphy's Law Book Two: More Reasons Why Things Go Wrong! (1980). It is unknown whether Hanlon knew of Heinlein's story or whether he independently constructed the phrase.[citation needed]

Hanlon's razor became well-known after its inclusion in the Jargon File, a glossary of computer programmer slang, since 1990. Later that same year, the Jargon File editors noted lack of knowledge about the term's derivation and the existence of a similar epigram by William James, though this was possibly intended as a reference to William James Laidlay. In 1996, the Jargon File entry on Hanlon's Razor noted the existence of the phrase in Heinlein's novella, with speculation that Hanlon's Razor might be a corruption of "Heinlein's Razor". The link to Murphy's law was described in a pair of 2001 blog entries by Quentin Stafford-Fraser, citing emails from Joseph E. Bigler. Subsequently, in 2002, the Jargon File entry noted the same. Current Jargon File refers to it as a "Murphyism".

The name was inspired by Occam's razor.
Answer: Hanlon's razor became well-known after its inclusion in the Jargon File, a glossary of computer programmer slang, since 1990.
Question: What formalism does Grail use?
Evidence: This chapter describes the underlying formalism of the theorem provers, as it is visible during an interactive proof trace, and present the general strategy followed by the theorem provers. The presentation in this chapter is somewhat informal, referring the reader elsewhere for full proofs.
The rest of this chapter is structured as follows. Section "Type-logical grammars" presents a general introduction to type-logical grammars and illustrates its basic concepts using the Lambek calculus, ending the section with some problems at the syntax-semantics interface for the Lambek calculus. Section "Modern type-logical grammars" looks at recent developments in type-logical grammars and how they solve some of the problems at the syntax-semantics interface. Section "Theorem proving" looks at two general frameworks for automated theorem proving for type-logical grammars, describing the internal representation of partial proofs and giving a high-level overview of the proof search mechanism.
Type-logical grammars are a family of grammar formalisms built on a foundation of logic and type theory. Type-logical grammars originated when BIBREF4 introduced his Syntactic Calculus (called the Lambek calculus, L, by later authors). Though Lambek built on the work of BIBREF5 , BIBREF6 and others, Lambek's main innovation was to cast the calculus as a logic, giving a sequent calculus and showing decidability by means of cut elimination. This combination of linguistic and computational applications has proved very influential.
This chapter describes the underlying formalism of the theorem provers, as it is visible during an interactive proof trace, and present the general strategy followed by the theorem provers. 
The rest of this chapter is structured as follows. Section "Type-logical grammars" presents a general introduction to type-logical grammars and illustrates its basic concepts using the Lambek calculus, ending the section with some problems at the syntax-semantics interface for the Lambek calculus.
Type-logical grammars are a family of grammar formalisms built on a foundation of logic and type theory. Type-logical grammars originated when BIBREF4 introduced his Syntactic Calculus (called the Lambek calculus, L, by later authors). Though Lambek built on the work of BIBREF5 , BIBREF6 and others, Lambek's main innovation was to cast the calculus as a logic, giving a sequent calculus and showing decidability by means of cut elimination.
Answer: The answers are shown as follows:
* a family of grammar formalisms built on a foundation of logic and type theory. Type-logical grammars originated when BIBREF4 introduced his Syntactic Calculus (called the Lambek calculus, L, by later authors).
Question: Who was Andrew Weatherall
Evidence: Andrew James Weatherall (6 April 1963 – 17 February 2020) was an English musician, DJ, songwriter, producer and remixer. His career took him from being one of the key DJs in the acid house movement of the late 1980s to being a remixer of tracks by the likes of Happy Mondays, New Order, Björk, the Orb, the Future Sound of London and My Bloody Valentine.

His production work on Primal Scream's album Screamadelica, adding samples, loops and creating an influential mix of hard rock, house and rave, helped the record win the first ever Mercury Music Prize in 1992 and become one of the most celebrated albums of the 1990s.
Answer: Andrew James Weatherall (6 April 1963 – 17 February 2020) was an English musician, DJ, songwriter, producer and remixer. His career took him from being one of the key DJs in the acid house movement of the late 1980s to being a remixer of tracks by the likes of Happy Mondays, New Order, Bjork, the Orb, the Future Sound of London and My Bloody Valentine.

His production work on Primal Scream's album Screamadelica, adding samples, loops and creating an influential mix of hard rock, house and rave, helped the record win the first ever Mercury Music Prize in 1992 and become one of the most celebrated albums of the 1990s.
Question: What are some typical attributes of a tortoiseshell cat?
Answer: Common attributes of a tortoiseshell (also referred to as "tortie") cat include golden eyes, a mottled coat that is mostly black and orange, and pink and/or black leathers. There is also an assumption that tortie cats are sassy, which is referenced as "tortietude."
Question: What is the first evidence of a boomerang?
Answer: Earliest evidence of the boomerang in Australia was about 20,000 years ago.
Question: Are there any documents with more than 5,000 words in the dataset collection?
Evidence: Table TABREF22 shows statistics of our datasets. It can be observed that average length of Fisher is much higher than 20 newsgroups and CSAT. Cumulative distribution of document lengths for each dataset is shown in Fig. FIGREF21. It can be observed that almost all of the documents in Fisher dataset have length more than 1000 words. For CSAT, more than 50% of the documents have length greater than 500 and for 20newsgroups only 10% of the documents have length greater than 500. Note that, for CSAT and 20newsgroups, there are few documents with length more than 5000.
Note that, for CSAT and 20newsgroups, there are few documents with length more than 5000.
Answer: Yes.
Question: Classify each of the following as being opaque or transparent: Window, wall, lens, glass, wood, cement
Answer: Window: Transparent
Wall: Opaque
Lens: Transparent
Glass: Transparent
Wood: Opaque
Cement: Opaque
Question: what were the baselines?
Evidence: We compare our system to a variety of baselines. (1) Rank by the number of times a citation is mentioned in the document. (2) Rank by the number of times the citation is cited in the literature (citation impact). (3) Rank using Google Scholar Related Articles. (4) Rank by the TF*IDF weighted cosine similarity. (5) Rank using a learning-to-rank model trained on text similarity rankings. The first two baseline systems are models where the values are ordered from highest to lowest to generate the ranking. The idea behind them is that the number of times a citation is mentioned in an article, or the citation impact may already be good indicators of their closeness. The text similarity model is trained using the same features and methods used by the annotation model, but trained using text similarity rankings instead of the author's judgments.
We compare our system to a variety of baselines. (1) Rank by the number of times a citation is mentioned in the document. (2) Rank by the number of times the citation is cited in the literature (citation impact). (3) Rank using Google Scholar Related Articles. (4) Rank by the TF*IDF weighted cosine similarity. (5) Rank using a learning-to-rank model trained on text similarity rankings. The first two baseline systems are models where the values are ordered from highest to lowest to generate the ranking. The idea behind them is that the number of times a citation is mentioned in an article, or the citation impact may already be good indicators of their closeness. The text similarity model is trained using the same features and methods used by the annotation model, but trained using text similarity rankings instead of the author's judgments.
Answer: The answers are shown as follows:
* Rank by the number of times a citation is mentioned in the document
*  Rank by the number of times the citation is cited in the literature (citation impact). 
* Rank using Google Scholar Related Articles.
* Rank by the TF*IDF weighted cosine similarity. 
* ank using a learning-to-rank model trained on text similarity rankings
Question: What was the previous state of the art model for this task?
Evidence: WAS: The architecture used in BIBREF3 without the audio input. The decoder output Chinese character at each timestep. Others keep unchanged to the original implementation.
LipCH-Net-seq: For a fair comparison, we use sequence-to-sequence with attention framework to replace the Connectionist temporal classification (CTC) loss BIBREF14 used in LipCH-Net BIBREF5 when converting picture to pinyin.
CSSMCM-w/o video: To evaluate the necessity of video information when predicting tone, the video stream is removed when predicting tone and Chinese characters. In other word, video is only used when predicting the pinyin sequence. The tone is predicted from the pinyin sequence. Tone information and pinyin information work together to predict Chinese character.
WAS: The architecture used in BIBREF3 without the audio input. The decoder output Chinese character at each timestep. Others keep unchanged to the original implementation.
LipCH-Net-seq: For a fair comparison, we use sequence-to-sequence with attention framework to replace the Connectionist temporal classification (CTC) loss BIBREF14 used in LipCH-Net BIBREF5 when converting picture to pinyin.
CSSMCM-w/o video: To evaluate the necessity of video information when predicting tone, the video stream is removed when predicting tone and Chinese characters. In other word, video is only used when predicting the pinyin sequence. The tone is predicted from the pinyin sequence. Tone information and pinyin information work together to predict Chinese character.
Answer: The answers are shown as follows:
* WAS
* LipCH-Net-seq
* CSSMCM-w/o video
Question: What improvement does the MOE model make over the SOTA on machine translation?
Evidence: Tables TABREF42 , TABREF43 , and TABREF44 show the results of our largest models, compared with published results. Our approach achieved BLEU scores of 40.56 and 26.03 on the WMT'14 En INLINEFORM0 Fr and En INLINEFORM1 De benchmarks. As our models did not use RL refinement, these results constitute significant gains of 1.34 and 1.12 BLEU score on top of the strong baselines in BIBREF3 . The perplexity scores are also better. On the Google Production dataset, our model achieved 1.01 higher test BLEU score even after training for only one sixth of the time.
As our models did not use RL refinement, these results constitute significant gains of 1.34 and 1.12 BLEU score on top of the strong baselines in BIBREF3 . The perplexity scores are also better. On the Google Production dataset, our model achieved 1.01 higher test BLEU score even after training for only one sixth of the time.
Answer: The answers are shown as follows:
* 1.34 and 1.12 BLEU score on top of the strong baselines in BIBREF3
* perplexity scores are also better
* On the Google Production dataset, our model achieved 1.01 higher test BLEU score
Question: Classify the following as either a solid, liquid, or gas: carbon dioxide, water, oil, granite, aluminum, gold, oxygen
Answer: Carbon Dioxide: Gas
Water: Liquid
Oil: Liquid
Granite: Solid
Aluminum: Solid
Gold: Solid
Oxygen: Gas
Question: Which characters belong to DC or Marvel Universe? Tigra, Cheetah
Answer: Tigra is Marvel, Cheetah is DC
Question: What does AWS stand for?
Answer: AWS is an abbreviation for Amazon Web Services. AWS is a subsidiary of Amazon and delivers cloud computing services.
Question: What are some arguments for decriminalizing people selling sex while criminalizing the purchasing of sex?
Answer: Sometimes minors are forced into prostitution, and should not be held criminally liable 
Many people in the sex trade want to leave that life and a criminal record impedes their progress
Turning to prostitution is often the last resort of a person who is impoverished, and poverty should not be against the law
If law enforcement depresses the demand for the sale of sex (by going after those who would buy sex), then prostitution rates may drop
Question: What problem does the new benchmark solve?
Evidence: The proliferation of the online social media has lately resulted in the democratization of online content sharing. Among other media, Twitter is very popular for research and application purposes due to its scale, representativeness and ease of public access to its content. However, tweets, that are short messages of up to 140 characters, pose several challenges to traditional Natural Language Processing (NLP) systems due to the creative use of characters and punctuation symbols, abbreviations ans slung language.
Named Entity Recognition (NER) is a fundamental step for most of the information extraction pipelines. Importantly, the terse and difficult text style of tweets presents serious challenges to NER systems, which are usually trained using more formal text sources such as newswire articles or Wikipedia entries that follow particular morpho-syntactic rules. As a result, off-the-self tools trained on such data perform poorly BIBREF0 . The problem becomes more intense as the number of entities to be identified increases, moving from the traditional setting of very few entities (persons, organization, time, location) to problems with more. Furthermore, most of the resources (e.g., software tools) and benchmarks for NER are for text written in English. As the multilingual content online increases, and English may not be anymore the lingua franca of the Web. Therefore, having resources and benchmarks in other languages is crucial for enabling information access worldwide.
In this paper, we propose a new benchmark for the problem of NER for tweets written in French. The tweets were collected using the publicly available Twitter API and annotated with 13 types of entities. The annotators were native speakers of French and had previous experience in the task of NER. Overall, the generated datasets consists of INLINEFORM0 tweets, split in training and test parts.
The paper is organized in two parts. In the first, we discuss the data preparation steps (collection, annotation) and we describe the proposed dataset. The dataset was first released in the framework of the CAp 2017 challenge, where 8 systems participated. Following, the second part of the paper presents an overview of baseline systems and the approaches employed by the systems that participated. We conclude with a discussion of the performance of Twitter NER systems and remarks for future work.
In this paper, we propose a new benchmark for the problem of NER for tweets written in French.
Answer: It solves the problem of Named Entity Recognition (NER) for tweets written in French.
Question: What makes an organization standout?
Answer: When an organization puts its people ahead of the profits and cares about the society it  creates a unique value and culture that produces long term results. There are many companies that are examples which include the TATA group, Reliance etc.
Question: What are all the way one can travel from Boston to Philadelphia
Answer: There are 3 mutually exclusive means of transport.
1. Air
2. Land
3. Sea

Within each option one can list a range of options. For example:
1. Air: take a commercial flight; take a private jet; fly yourself; take a hot air balloon, etc.
2. Land: walk, run, drive, ride a bus, ride a bike, ride a motorcycle, hitch hike, use a roller skate, train, etc.
3. Sea: swim, ride a personal boat, take a commercial boat ride, etc.
Question: Which of the tree species mentioned in the text are used as a source of food for humans?
Evidence: Multipurpose trees or multifunctional trees are trees that are deliberately grown and managed for more than one output. They may supply food in the form of fruit, nuts, or leaves that can be used as a vegetable; while at the same time supplying firewood, adding nitrogen to the soil, or supplying some other combination of multiple outputs. "Multipurpose tree" is a term common to agroforestry, particularly when speaking of tropical agroforestry where the tree owner is a subsistence farmer.

While all trees can be said to serve several purposes, such as providing habitat, shade, or soil improvement; multipurpose trees have a greater impact on a farmer's well-being because they fulfill more than one basic human need. In most cases multipurpose trees have a primary role; such as being part of a living fence, or a windbreak, or used in an ally cropping system. In addition to this they will have one or more secondary roles, most often supplying a family with food or firewood, or both.

When a multipurpose tree is planted, a number of needs and functions can be fulfilled at once. They may be used as a windbreak, while also supplying a staple food for the owner. They may be used as fencepost in a living fence, while also being the main source of firewood for the owner. They may be intercropped into existing fields, to supply nitrogen to the soil, and at the same time serve as a source of both food and firewood.

Common multipurpose trees of the tropics include:

Gliricidia (Gliricidia sepium) – the most common tree used for living fences in Central America, firewood, fodder, fixing nitrogen into the soil.
Moringa (Moringa oleifera) – edible leaves, pods and beans, commonly used for animal forage and shade (it does not fix nitrogen as is commonly believed)
Coconut palm (Cocos nucifera) – used for food, purified water (juice from inside the coconut), roof thatching, firewood, shade.
Neem (Azadirachta indica) – limited use as insect repellent, antibiotic, adding nitrogen to the soil, windbreaks, biomass production for use as mulch, firewood.
Ideally most trees found on tropical farms should be multipurpose, and provide more to the farmer than simply shade and firewood. In most cases they should be nitrogen fixing legumes, or trees that greatly increase the farmer's food security.
Answer: Moringa(Moringa oleifera) and Coconut palm (Cocos nucifera) are used as a source of food for humans.
Question: Why does Israel offer huge discounts to Chicago Booth students' spring break trips?
Answer: Israel wants to sell their country to potential future leaders of the U.S. They know that we write them hefty checks every year and they don't want that to stop. Israel knows that by taking Chicago Booth students around their country and providing a narrative from a Jew's perspective, will likely get them to see their point of view and be on their side in the future. It's actually quite a smart initiative.
Question: Is the Earth round?
Answer: The planet Earth is generally considered to be round, although it is not a perfect sphere. The poles are slightly depressed, making the Earth slightly thicker around the equator.
Question: Who is the singer in Bon Iver?
Evidence: Bon Iver (/ˌboʊn iːˈvɛər/ BOHN ee-VAIR) is an American indie folk band founded in 2006 by singer-songwriter Justin Vernon.
Answer: Justin Vernon is the singer-songwriter in Bon Iver.
Question: From the passage provided, extract the cost of the Ryman Auditorium's most recent renovation and expansion.
Evidence: In 2015, the Ryman underwent another US$14,000,000 (equivalent to $16,004,773 in 2021) renovation and expansion. Much of the 1994 expansion was gutted and remodeled. The original building received only minor touch-ups and remained in use throughout the construction. The renovation and expansion includes more lobby space, plus expanded restrooms, concessions, and a gift shop. A new quick-service restaurant was added, called "Cafe Lula" and named in memory of Lula C. Naff. (The cafe closed in 2020 due to the COVID-19 pandemic, and was not reopened.) New renovations in 2023 will include a new gift shop in the previous Café Lula location.  

Also added in the 2015 renovations was a 100-seat theater. Here a short holographic film is shown that serves as the first exhibit on the building's daily self-guided tours. Entitled The Soul Of Nashville, the film features an actress portraying Naff in presenting the history of the Ryman. It also features an original song performed by Darius Rucker, Sheryl Crow, Vince Gill, and the Fisk Jubilee Singers.
Answer: In 2015, the Ryman underwent another US$14,000,000 (equivalent to $16,004,773 in 2021) renovation and expansion.
Question: Is the capital city and the largest city of Chile same or different?
Evidence: Chile, officially the Republic of Chile, is a country located in western South America. It is the southernmost country in the world and closest to Antarctica, stretching along a narrow strip of land between the Andes Mountains and the Pacific Ocean. With an area of 756,096 square kilometers (291,930 sq mi) and a population of 17.5 million as of 2017, Chile shares borders with Peru to the north, Bolivia to the northeast, Argentina to the east, and the Drake Passage to the south. The country also controls several Pacific islands, including Juan Fernández, Isla Salas y Gómez, Desventuradas, and Easter Island, and claims about 1,250,000 square kilometers (480,000 sq mi) of Antarctica as the Chilean Antarctic Territory.[nb 2] The capital and largest city of Chile is Santiago, and the national language is Spanish.
Answer: They are the same. Santiago.
Question: Name the person  from Bangladesh who won Pulitzer Prize 2022
Answer: Fahmida Azim(Painter and story writer)
Question: What are some high-potential cryptos with low marketcaps?
Answer: 1) Morpheus Network - $MNW
2) Greenheart - $CBD
3) Realio - $RIO
4) Blocksquare - $BST
5) Theopetra - $THEO
6) Constellation - $DAG
7) Render - $RNDR
8) Alkimi - $ADS
9) Verasity - $VRA
10) Chainge Finance - $CHNG
Question: Please list a few of the professional organizations that Judith Stern participated in during her career.
Evidence: In 1974, Judith Stern joined the faculty of the University of California, Davis as an assistant professor in the Department of Nutrition. There her early research centered on differences in the adipose tissue of obese individuals – using Zucker rats as a research model. Eventually her research program grew to include human studies, focused on various obesity treatment regimens.

In 1995, Stern was elected to the National Academy of Medicine. At various points she was elected president of the NAASO (1992–1993, now The Obesity Society) and the American Society for Clinical Nutrition. Stern co-founded the American Obesity Association, an advocacy group that lobbied in favor of obesity research and treatment.
Answer: Some of the professional organizations that Judith Stern created or participated in are the National Academy of Medicine, the Obesity Society, and the American Society for Clinical Nutrition.