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 "incorporating relation paths in neural relation extraction"):
  Abstract: Distantly supervised relation extraction has been widely used to find novel relational facts from plain text. To predict the relation between a pair of two target entities, existing methods solely rely on those direct sentences containing both entities. In fact, there are also many sentences containing only one of the target entities, which provide rich and useful information for relation extraction. To address this issue, we build inference chains between two target entities via intermediate entities, and propose a path-based neural relation extraction model to encode the relational semantics from both direct sentences and inference chains. Experimental results on real-world datasets show that, our model can make full use of those sentences containing only one target entity, and achieves significant and consistent improvements on relation extraction as compared with baselines.

Includes members:
  Member "semeval 2010 task 8 multi way classification of semantic relations between pairs of nominals":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning from explanations with neural execution tree")
  Member "jointly extracting relations with class ties via effective deep ranking":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "relation adversarial network for low resource knowledgegraph completion")
  Member "chains of reasoning over entities relations and text using recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "query2box reasoning over knowledge graphs in vector space using box embeddings")
  Member "knowledge representation via joint learning of sequential text and knowledge graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bayes embedding bem refining representation by integrating knowledge graphs and behavior specific networks")
  Member "end to end relation extraction using lstms on sequences and tree structures":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deeper task specificity improves joint entity and relation extraction")
  Member "a neural attention model for abstractive sentence summarization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a 3 accelerating attention mechanisms in neural networks with approximation")
  Member "modeling relation paths for representation learning of knowledge bases":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "knowledge graph embedding for link prediction a comparative analysis")
  Member "classifying relations by ranking with convolutional neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")

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)