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 "scalable neural methods for reasoning with a symbolic knowledge base"):
  Abstract: We describe a novel way of representing a symbolic knowledge base (KB) called a sparse-matrix reified KB. This representation enables neural modules that are fully differentiable, faithful to the original semantics of the KB, expressive enough to model multi-hop inferences, and scalable enough to use with realistically large KBs. The sparse-matrix reified KB can be distributed across multiple GPUs, can scale to tens of millions of entities and facts, and is orders of magnitude faster than naive sparse-matrix implementations. The reified KB enables very simple end-to-end architectures to obtain competitive performance on several benchmarks representing two families of tasks: KB completion, and learning semantic parsers from denotations.

Includes members:
  Member "generating logical forms from graph representations of text and entities":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "answering conversational questions on structured data without logical forms")
  Member "pullnet open domain question answering with iterative retrieval on knowledge bases and text":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "differentiable reasoning over a virtual knowledge base")
  Member "neural query language a knowledge base query language for tensorflow":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "differentiable reasoning over a virtual knowledge base")
  Member "seq2sql generating structured queries from natural language using reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exploring neural models for parsing natural language into first order logic")
  Member "policy shaping and generalized update equations for semantic parsing from denotations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "introduction to neural network based approaches for question answering over knowledge graphs")
  Member "neural compositional denotational semantics for question answering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "break it down a question understanding benchmark")
  Member "improving text to sql evaluation methodology":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning semantic parsers from denotations with latent structured alignments and abstract programs")
  Member "embedding logical queries on knowledge graphs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "evaluating logical generalization in graph neural networks")

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)