@article{Stede2020,
  author    = {Stede, Manfred},
  title     = {From connectives to coherence relations},
  series = {Revue roumaine de linguistique : RRL = Romanian review of linguistics},
  volume    = {65},
  journal   = {Revue roumaine de linguistique : RRL = Romanian review of linguistics},
  number    = {3},
  publisher = {Ed. Academiei Rom{\^a}ne},
  address   = {Bucure{\c{s}}ti},
  issn      = {0035-3957},
  pages     = {213 -- 233},
  year      = {2020},
  abstract  = {The notion of coherence relations is quite widely accepted in general, but concrete proposals differ considerably on the questions of how they should be motivated, which relations are to be assumed, and how they should be defined. This paper takes a "bottom-up" perspective by assessing the contribution made by linguistic signals (connectives), using insights from the relevant literature as well as verification by practical text annotation. We work primarily with the German language here and focus on the realm of contrast. Thus, we suggest a new inventory of contrastive connective functions and discuss their relationship to contrastive coherence relations that have been proposed in earlier work.},
  language  = {en}
}
@misc{SaintDizierStede2017,
  author    = {Saint-Dizier, Patrick and Stede, Manfred},
  title     = {Foundations of the language of argumentation},
  series = {Argument \& computation},
  volume    = {8},
  journal   = {Argument \& computation},
  number    = {2 Special issue},
  publisher = {IOS Press},
  address   = {Amsterdam},
  issn      = {1946-2166},
  doi       = {10.3233/AAC-170018},
  pages     = {91 -- 93},
  year      = {2017},
  language  = {en}
}
@misc{AfantenosPeldszusStede2018,
  author    = {Afantenos, Stergos and Peldszus, Andreas and Stede, Manfred},
  title     = {Comparing decoding mechanisms for parsing argumentative structures},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1062},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-47052},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-470527},
  pages     = {18},
  year      = {2018},
  abstract  = {Parsing of argumentative structures has become a very active line of research in recent years. Like discourse parsing or any other natural language task that requires prediction of linguistic structures, most approaches choose to learn a local model and then perform global decoding over the local probability distributions, often imposing constraints that are specific to the task at hand. Specifically for argumentation parsing, two decoding approaches have been recently proposed: Minimum Spanning Trees (MST) and Integer Linear Programming (ILP), following similar trends in discourse parsing. In contrast to discourse parsing though, where trees are not always used as underlying annotation schemes, argumentation structures so far have always been represented with trees. Using the 'argumentative microtext corpus' [in: Argumentation and Reasoned Action: Proceedings of the 1st European Conference on Argumentation, Lisbon 2015 / Vol. 2, College Publications, London, 2016, pp. 801-815] as underlying data and replicating three different decoding mechanisms, in this paper we propose a novel ILP decoder and an extension to our earlier MST work, and then thoroughly compare the approaches. The result is that our new decoder outperforms related work in important respects, and that in general, ILP and MST yield very similar performance.},
  language  = {en}
}
@article{AfantenosPeldszusStede2018,
  author    = {Afantenos, Stergos and Peldszus, Andreas and Stede, Manfred},
  title     = {Comparing decoding mechanisms for parsing argumentative structures},
  series = {Argument \& Computation},
  volume    = {9},
  journal   = {Argument \& Computation},
  number    = {3},
  publisher = {IOS Press},
  address   = {Amsterdam},
  issn      = {1946-2166},
  doi       = {10.3233/AAC-180033},
  pages     = {177 -- 192},
  year      = {2018},
  abstract  = {Parsing of argumentative structures has become a very active line of research in recent years. Like discourse parsing or any other natural language task that requires prediction of linguistic structures, most approaches choose to learn a local model and then perform global decoding over the local probability distributions, often imposing constraints that are specific to the task at hand. Specifically for argumentation parsing, two decoding approaches have been recently proposed: Minimum Spanning Trees (MST) and Integer Linear Programming (ILP), following similar trends in discourse parsing. In contrast to discourse parsing though, where trees are not always used as underlying annotation schemes, argumentation structures so far have always been represented with trees. Using the 'argumentative microtext corpus' [in: Argumentation and Reasoned Action: Proceedings of the 1st European Conference on Argumentation, Lisbon 2015 / Vol. 2, College Publications, London, 2016, pp. 801-815] as underlying data and replicating three different decoding mechanisms, in this paper we propose a novel ILP decoder and an extension to our earlier MST work, and then thoroughly compare the approaches. The result is that our new decoder outperforms related work in important respects, and that in general, ILP and MST yield very similar performance.},
  language  = {en}
}