Input: Read this: From the Rigveda until the time of Pāṇini (fourth century BCE) the development of the early Vedic language can be observed in other Vedic texts: the Samaveda, Yajurveda, Atharvaveda, Brahmanas, and Upanishads. During this time, the prestige of the language, its use for sacred purposes, and the importance attached to its correct enunciation all served as powerful conservative forces resisting the normal processes of linguistic change. However, there is a clear, five-level linguistic development of Vedic from the Rigveda to the language of the Upanishads and the earliest sutras such as the Baudhayana sutras.
Question: How was Sanskrit viewed to be in relation to maintaining class?

Output: conservative


Input: Read this: In some jurisdictions, copyright or the right to enforce it can be contractually assigned to a third party which did not have a role in producing the work. When this outsourced litigator appears to have no intention of taking any copyright infringement cases to trial, but rather only takes them just far enough through the legal system to identify and exact settlements from suspected infringers, critics commonly refer to the party as a "copyright troll." Such practices have had mixed results in the U.S.
Question: Who can be assigned a contract to enforce a copyright in all jurisdictions?

Output: unanswerable


Input: Read this: Setting national renewable energy targets can be an important part of a renewable energy policy and these targets are usually defined as a percentage of the primary energy and/or electricity generation mix. For example, the European Union has prescribed an indicative renewable energy target of 12 per cent of the total EU energy mix and 22 per cent of electricity consumption by 2010. National targets for individual EU Member States have also been set to meet the overall target. Other developed countries with defined national or regional targets include Australia, Canada, Israel, Japan, Korea, New Zealand, Norway, Singapore, Switzerland, and some US States.
Question: Name one outher country with defined national or regional target?

Output: Australia


Input: Read this: Genetics compression algorithms are the latest generation of lossless algorithms that compress data (typically sequences of nucleotides) using both conventional compression algorithms and genetic algorithms adapted to the specific datatype. In 2012, a team of scientists from Johns Hopkins University published a genetic compression algorithm that does not use a reference genome for compression. HAPZIPPER was tailored for HapMap data and achieves over 20-fold compression (95% reduction in file size), providing 2- to 4-fold better compression and in much faster time than the leading general-purpose compression utilities. For this, Chanda, Elhaik, and Bader introduced MAF based encoding (MAFE), which reduces the heterogeneity of the dataset by sorting SNPs by their minor allele frequency, thus homogenizing the dataset. Other algorithms in 2009 and 2013 (DNAZip and GenomeZip) have compression ratios of up to 1200-fold—allowing 6 billion basepair diploid human genomes to be stored in 2.5 megabytes (relative to a reference genome or averaged over many genomes).
Question: What encoding reduces the heterogenelty of a dataset by sorting megabytes?

Output:
unanswerable