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 "a question entailment approach to question answering"):
  Abstract: Background#R##N#One of the challenges in large-scale information retrieval (IR) is developing fine-grained and domain-specific methods to answer natural language questions. Despite the availability of numerous sources and datasets for answer retrieval, Question Answering (QA) remains a challenging problem due to the difficulty of the question understanding and answer extraction tasks. One of the promising tracks investigated in QA is mapping new questions to formerly answered questions that are “similar”.

Includes members:
  Member "semeval 2016 task 3 community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "review guided helpful answer identification in e commerce")
  Member "semeval 2017 task 3 community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a pilot study on multiple choice machine reading comprehension for vietnamese texts")
  Member "semantic sentence matching with densely connected recurrent and co attentive information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "utilizing bert intermediate layers for aspect based sentiment analysis and natural language inference")
  Member "dr bilstm dependent reading bidirectional lstm for natural language inference":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "kernel graph attention network for fact verification")
  Member "neural natural language inference models enhanced with external knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sequential neural networks for noetic end to end response selection")
  Member "supervised learning of universal sentence representations from natural language inference data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey on contextual embeddings")
  Member "cmu livemedqa at trec 2017 liveqa a consumer health question answering system":
    also connected through other hyperedges:
      (none)
  Member "neural question answering at bioasq 5b":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "uncc biomedical semantic question answering systems bioasq task 7b phase b")

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)