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 "learning structured natural language representations for semantic parsing"):
  Abstract: We introduce a neural semantic parser that converts natural language utterances to intermediate representations in the form of predicate-argument structures, which are induced with a transition system and subsequently mapped to target domains. The semantic parser is trained end-to-end using annotated logical forms or their denotations. We obtain competitive results on various datasets. The induced predicate-argument structures shed light on the types of representations useful for semantic parsing and how these are different from linguistically motivated ones.

Includes members:
  Member "recurrent neural network grammars":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hierarchical character embeddings learning phonological and semantic representations in languages of logographic origin using recursive neural networks")
  Member "evaluating induced ccg parsers on grounded semantic parsing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning cross context entity representations from text")
  Member "learning a natural language interface with neural programmer":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "plotqa reasoning over scientific plots")
  Member "rationalizing neural predictions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "description based text classification with reinforcement learning")
  Member "data recombination for neural semantic parsing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exploring neural models for parsing natural language into first order logic")
  Member "no need to pay attention simple recurrent neural networks work for answering simple questions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "using context information to enhance simple question answering")
  Member "semantic parsing with semi supervised sequential autoencoders":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exploring neural models for parsing natural language into first order logic")
  Member "question answering on freebase via relation extraction and textual evidence":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "realistic re evaluation of knowledge graph completion methods an experimental study")

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)