human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "word sense disambiguation a survey"
  Abstract: In this paper, we made a survey on Word Sense Disambiguation (WSD). Near about in all major languages around the world, research in WSD has been conducted upto different extents. In this paper, we have gone through a survey regarding the different approaches adopted in different research works, the State of the Art in the performance in this domain, recent works in different Indian languages and finally a survey in Bengali language. We have made a survey on different competitions in this field and the bench mark results, obtained from those competitions.

Connected through hyperedge HE-1 (induced by source paper "pun gan generative adversarial network for pun generation"):
  with members:
    - "pun generation with surprise"
    - "incorporating glosses into neural word sense disambiguation"
    - "long text generation via adversarial training with leaked information"
    - "a deep reinforced model for abstractive summarization"
    - "seqgan sequence generative adversarial nets with policy gradient"
    - "improved techniques for training gans"
    - "word sense disambiguation using a bidirectional lstm"

Connected through hyperedge HE-2 (induced by source paper "visual genome connecting language and vision using crowdsourced dense image annotations"):
  with members:
    - "embracing error to enable rapid crowdsourcing"
    - "yfcc100m the new data in multimedia research"
    - "exploring models and data for image question answering"
    - "vqa visual question answering"
    - "visual madlibs fill in the blank image generation and question answering"
    - "phrase based image captioning"
    - "learning to answer questions from image using convolutional neural network"
    - "equilibrated adaptive learning rates for non convex optimization"

Question: Please tell me which class the center node 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)