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 "semeval 2016 task 3 community question answering"):
  Abstract: This paper describes the SemEval--2016 Task 3 on Community Question Answering, which we offered in English and Arabic. For English, we had three subtasks: Question--Comment Similarity (subtask A), Question--Question Similarity (B), and Question--External Comment Similarity (C). For Arabic, we had another subtask: Rerank the correct answers for a new question (D). Eighteen teams participated in the task, submitting a total of 95 runs (38 primary and 57 contrastive) for the four subtasks. A variety of approaches and features were used by the participating systems to address the different subtasks, which are summarized in this paper. The best systems achieved an official score (MAP) of 79.19, 76.70, 55.41, and 45.83 in subtasks A, B, C, and D, respectively. These scores are significantly better than those for the baselines that we provided. For subtask A, the best system improved over the 2015 winner by 3 points absolute in terms of Accuracy.

Includes members:
  Member "hunting for troll comments in news community forums":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "detecting toxicity in news articles application to bulgarian")
  Member "semeval 2015 task 3 answer selection in community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "training neural response selection for task oriented dialogue systems")
  Member "global thread level inference for comment classification in community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "semeval 2017 task 3 community question answering")
  Member "semanticz at semeval 2016 task 3 ranking relevant answers in community question answering using semantic similarity based on fine tuned word embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "automatic fact checking using context and discourse information")
  Member "pairwise neural machine translation evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sentence level human translation quality estimation with attention based neural networks")
  Member "machine translation evaluation meets community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a joint model for multimodal document quality assessment")
  Member "uh prhlt at semeval 2016 task 3 combining lexical and semantic based features for community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "query expansion for cross language question re ranking")
  Member "answer sequence learning with neural networks for answer selection in community question answering":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a joint model for multimodal document quality assessment")

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)