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 "joint extraction of entities and relations based on a novel decomposition strategy"):
  Abstract: Joint extraction of entities and relations aims to detect entity pairs along with their relations using a single model. Prior works typically solve this task in the extract-then-classify or unified labeling manner. However, these methods either suffer from the redundant entity pairs, or ignore the important inner structure in the process of extracting entities and relations. To address these limitations, in this paper, we first decompose the joint extraction task into two inner-related subtasks, namely HE extraction and TER extraction. The former subtask is to distinguish all head-entities that may be involved with target relations, and the latter is to identify corresponding tail-entities and relations for each extracted head-entity. Next, these two subtasks are further deconstructed into several sequence labeling problems based on our proposed span-based tagging scheme, which are conveniently solved by a hierarchical boundary tagger and a multi-span decoding algorithm. Owing to the reasonable decomposition strategy, our model can fully capture the semantic interdependency between different steps, as well as reduce noise from irrelevant entity pairs.Experimental results show that our method outperforms previous work by 5.6%, 17.2% and 3.7% (F1 score), achieving a new state-of-the-art on three public datasets.

Includes members:
  Member "porous lattice based transformer encoder for chinese ner":
    also connected through other hyperedges:
      (none)
  Member "entity relation extraction as multi turn question answering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "description based text classification with reinforcement learning")
  Member "open domain targeted sentiment analysis via span based extraction and classification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exploiting bert for end to end aspect based sentiment analysis")
  Member "sentiment tagging with partial labels using modular architectures":
    also connected through other hyperedges:
      (none)
  Member "adversarial training for multi context joint entity and relation extraction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "span based joint entity and relation extraction with transformer pre training")
  Member "a hierarchical framework for relation extraction with reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "entity relation extraction as multi turn question answering")
  Member "joint extraction of entities and relations based on a novel tagging scheme":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "hybrid neural tagging model for open relation extraction")
  Member "heterogeneous supervision for relation extraction a representation learning approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "keml a knowledge enriched meta learning framework for lexical relation classification")

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)