Automatic detection of arguments in legal texts

By Marie-Francine Moens, Erik Boiy, Raquel Mochales Palau, Chris Reed. International Conference on Artificial Intelligence and Law, 2007

305 citations recorded by the source corpus.

How researchers see this paper

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Argument Mining: A Survey (2020, methodology): “One of the first approaches to argument mining, and perhaps still the most developed, is the work carried out by Moens et al. (Moens et al. 2007; Palau and Moens 2009; Mochales and Moens 2011), which first attempts to detect the argumentative parts of a text by first splitting the text into sentence”
Identifying Argumentative Discourse Structures in Persuasive Essays (2014, background): “For instance, the argumentation scheme proposed by Peldszus and Stede (2013) includes three argumentative relations (support, attack and counter-attack), whereas Stab and Gurevych (2014) propose a scheme including only two relations (support and attack).”
Corpus Wide Argument Mining - a Working Solution (2019, background): “In addition to legal documents (Moens et al. 2007; Wyner et al. 2010; Grabmair et al. 2015), examples also include student essays (Stab, Miller, and Gurevych 2018; Persing and Ng 2016), user comments on proposed regulations (Park and Cardie 2014) and newspaper articles (Feng and Hirst 2011).”
Argumentation mining (2011, methodology): “We used the features presented in Table 6 and we obtained nearly 73% accuracy when detecting argumentation in the Araucaria corpus [20].”
Argumentation mining: the detection, classification and structure of arguments in text (2009, methodology): “We obtained nearly 73% accuracy when detecting arguments in the Araucaria corpus [19].”