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 "using sentence plausibility to learn the semantics of transitive verbs"):
  Abstract: The functional approach to compositional distributional semantics considers transitive verbs to be linear maps that transform the distributional vectors representing nouns into a vector representing a sentence. We conduct an initial investigation that uses a matrix consisting of the parameters of a logistic regression classifier trained on a plausibility task as a transitive verb function. We compare our method to a commonly used corpus-based method for constructing a verb matrix and find that the plausibility training may be more effective for disambiguation tasks.

Includes members:
  Member "a study of entanglement in a categorical framework of natural language":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the mathematics of text structure")
  Member "multi step regression learning for compositional distributional semantics":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "revisiting paraphrase question generator using pairwise discriminator")
  Member "adadelta an adaptive learning rate method":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hyper parameter optimization a review of algorithms and applications")
  Member "experimental support for a categorical compositional distributional model of meaning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "incremental monoidal grammars")
  Member "experimenting with transitive verbs in a discocat":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "collaborative training of tensors for compositional distributional semantics")
  Member "mathematical foundations for a compositional distributional model of meaning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "tensor networks for language modeling")

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)