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 "providing advanced access to historical war memoirs through the identification of events participants and roles"):
  Abstract: The progressive digitization of historical archives provides new, often domain specific, textual resources that report on facts and events happened in the past; among them, memoirs are a very common type of primary source. In this paper, we present an approach for extracting information from historical war memoirs and turning it into structured knowledge. This is based on the semantic notions of events, participants and roles. We assess quantitatively each of the key-steps of our approach and provide a graph-based representation of the extracted knowledge, which allows the end user to move between close and distant reading of the collection.

Includes members:
  Member "extracting event centric document collections from large scale web archives":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "data4urbanmobility towards holistic data analytics for mobility applications in urban regions")
  Member "italy goes to stanford a collection of corenlp modules for italian":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cross lingual abstract meaning representation parsing")
  Member "enriching word vectors with subword information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "exploring the political agenda of the european parliament using a dynamic topic modeling approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "two computational models for analyzing political attention in social media")
  Member "distributed representations of words and phrases and their compositionality":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")

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)