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 "word sense disambiguation for 158 languages using word embeddings only"):
  Abstract: Disambiguation of word senses in context is easy for humans, but is a major challenge for automatic approaches. Sophisticated supervised and knowledge-based models were developed to solve this task. However, (i) the inherent Zipfian distribution of supervised training instances for a given word and/or (ii) the quality of linguistic knowledge representations motivate the development of completely unsupervised and knowledge-free approaches to word sense disambiguation (WSD). They are particularly useful for under-resourced languages which do not have any resources for building either supervised and/or knowledge-based models. In this paper, we present a method that takes as input a standard pre-trained word embedding model and induces a fully-fledged word sense inventory, which can be used for disambiguation in context. We use this method to induce a collection of sense inventories for 158 languages on the basis of the original pre-trained fastText word embeddings by Grave et al. (2018), enabling WSD in these languages. Models and system are available online.

Includes members:
  Member "glossbert bert for word sense disambiguation with gloss knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "what does my qa model know devising controlled probes using expert knowledge")
  Member "multi sense embeddings from topic models":
    also connected through other hyperedges:
      (none)
  Member "watset local global graph clustering with applications in sense and frame induction":
    also connected through other hyperedges:
      (none)
  Member "an unsupervised word sense disambiguation system for under resourced languages":
    also connected through other hyperedges:
      (none)
  Member "joint multilingual supervision for cross lingual entity linking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improving candidate generation for low resource cross lingual entity linking")
  Member "russian word sense induction by clustering averaged word embeddings":
    also connected through other hyperedges:
      (none)
  Member "autosense model for word sense induction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards better substitution based word sense induction")
  Member "word sense induction with neural bilm and symmetric patterns":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "still a pain in the neck evaluating text representations on lexical composition")

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)