human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "hotpotqa a dataset for diverse explainable multi hop question answering"):
  Abstract: Existing question answering (QA) datasets fail to train QA systems to perform complex reasoning and provide explanations for answers. We introduce HotpotQA, a new dataset with 113k Wikipedia-based question-answer pairs with four key features: (1) the questions require finding and reasoning over multiple supporting documents to answer; (2) the questions are diverse and not constrained to any pre-existing knowledge bases or knowledge schemas; (3) we provide sentence-level supporting facts required for reasoning, allowing QA systems to reason with strong supervision and explain the predictions; (4) we offer a new type of factoid comparison questions to test QA systems' ability to extract relevant facts and perform necessary comparison. We show that HotpotQA is challenging for the latest QA systems, and the supporting facts enable models to improve performance and make explainable predictions.

Includes members:
  Member "the web as a knowledge base for answering complex questions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "natural language qa approaches using reasoning with external knowledge")
  Member "know what you don t know unanswerable questions for squad":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "description based text classification with reinforcement learning")
  Member "contextualized word representations for reading comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "making neural machine reading comprehension faster")
  Member "memen multi layer embedding with memory networks for machine comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "triviaqa a large scale distantly supervised challenge dataset for reading comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "searchqa a new q a dataset augmented with context from a search engine":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "stochastic answer networks for machine reading comprehension":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "parlai a dialog research software platform":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "emptransfo a multi head transformer architecture for creating empathetic dialog systems")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CL(Computation and Language)