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 survey of cross lingual features for zero shot cross lingual semantic parsing"):
  Abstract: The availability of corpora to train semantic parsers in English has lead to significant advances in the field. Unfortunately, for languages other than English, annotation is scarce and so are developed parsers. We then ask: could a parser trained in English be applied to language that it hasn't been trained on? To answer this question we explore zero-shot cross-lingual semantic parsing where we train an available coarse-to-fine semantic parser (Liu et al., 2018) using cross-lingual word embeddings and universal dependencies in English and test it on Italian, German and Dutch. Results on the Parallel Meaning Bank - a multilingual semantic graphbank, show that Universal Dependency features significantly boost performance when used in conjunction with other lexical features but modelling the UD structure directly when encoding the input does not.

Includes members:
  Member "polyglot semantic role labeling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "semantic role labeling with iterative structure refinement")
  Member "cross lingual semantic parsing":
    also connected through other hyperedges:
      (none)
  Member "exploring neural methods for parsing discourse representation structures":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "don t parse generate a sequence to sequence architecture for task oriented semantic parsing")
  Member "evaluating scoped meaning representations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exploring neural methods for parsing discourse representation structures")
  Member "coarse to fine decoding for neural semantic parsing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "structural language models of code")
  Member "neural networks for cross lingual negation scope detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "negbert a transfer learning approach for negation detection and scope resolution")
  Member "universal semantic parsing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reasoning driven question answering for natural language understanding")
  Member "cross lingual abstract meaning representation parsing":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "amr parsing as sequence to graph transduction")

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)