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 study of entanglement in a categorical framework of natural language"):
  Abstract: In both quantum mechanics and corpus linguistics based on vector spaces, the notion of entanglement provides a means for the various subsystems to communicate with each other. In this paper we examine a number of implementations of the categorical framework of Coecke et al. [4] for natural language, from an entanglement perspective. Specifically, our goal is to better understand in what way the level of entanglement of the relational tensors (or t he lack of it) affects the compositional structures in practical situations. Our findings reveal tha t a number of proposals for verb construction lead to almost separable tensors, a fact that considerably s implifies the interactions between the words. We examine the ramifications of this fact, and we show t hat the use of Frobenius algebras mitigates the potential problems to a great extent. Finally, we briefly examine a machine learning method that creates verb tensors exhibiting a sufficient lev el of entanglement.

Includes members:
  Member "the frobenius anatomy of word meanings ii possessive relative pronouns":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "the mathematics of text structure")
  Member "resolving lexical ambiguity in tensor regression models of meaning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "determining semantic textual similarity using natural deduction proofs")
  Member "reasoning about meaning in natural language with compact closed categories and frobenius algebras":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the mathematics of text structure")
  Member "the frobenius anatomy of word meanings i subject and object relative pronouns":
    also connected through other hyperedges:
      - Hyperedge HE-4 (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-5 (induced by source paper "revisiting paraphrase question generator using pairwise discriminator")
  Member "experimental support for a categorical compositional distributional model of meaning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "incremental monoidal grammars")
  Member "experimenting with transitive verbs in a discocat":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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-8 (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)