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: "estimators for stochastic unification based grammars"
  Abstract: Log-linear models provide a statistically sound framework for Stochastic ``Unification-Based'' Grammars (SUBGs) and stochastic versions of other kinds of grammars. We describe two computationally-tractable ways of estimating the parameters of such grammars from a training corpus of syntactic analyses, and apply these to estimate a stochastic version of Lexical-Functional Grammar.

Connected through hyperedge HE-1 (induced by source paper "worst case polynomial time exact map inference on discrete models with global dependencies"):
  with members:
    - "optimizing for measure of performance in max margin parsing"
    - "a comparative study of modern inference techniques for structured discrete energy minimization problems"
    - "a compact linear programming relaxation for binary sub modular mrf"
    - "tighter linear program relaxations for high order graphical models"
    - "discriminative probabilistic models for relational data"
    - "fast exact inference for recursive cardinality models"
    - "a tutorial on dual decomposition and lagrangian relaxation for inference in natural language processing"
    - "tightening lp relaxations for map using message passing"

Connected through hyperedge HE-2 (induced by source paper "learning to map sentences to logical form structured classification with probabilistic categorial grammars"):
  with members:
    - "acquiring word meaning mappings for natural language interfaces"

Connected through hyperedge HE-3 (induced by source paper "exponential families for conditional random fields"):
  with members:
    - "the use of classifiers in sequential inference"

Connected through hyperedge HE-4 (induced by source paper "probabilistic top down parsing and language modeling"):
  with members:
    - "exploiting syntactic structure for natural language modeling"
    - "exploiting diversity in natural language processing combining parsers"
    - "recognition performance of a structured language model"
    - "efficient probabilistic top down and left corner parsing"
    - "measuring efficiency in high accuracy broad coverage statistical parsing"
    - "refinement of a structured language model"
    - "expoiting syntactic structure for language modeling"

Connected through hyperedge HE-5 (induced by source paper "exploiting auxiliary distributions in stochastic unification based grammars"):
  with members:
    - "inducing a semantically annotated lexicon via em based clustering"

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)