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2019
Rice, Douglas (2019): Understanding Legal Meaning through Word Embeddings. In: SSRN Electronic Journal. DOI: 10.2139/ssrn.3455747

DOI: https://doi.org/10.2139/ssrn.3455747

Abstract: For judges and legal scholars, the quest for meaning and the identification of methods appropriate for understanding word meaning animates volumes upon volumes of debate. Likewise, social scientists interested in studying the law have increasingly recognized the variations in choices over words as important barometers for understanding the law. In this paper, I suggest recent advances in computational linguistics -- notably, the efficient estimation of distributed representations of word meanings, or word embeddings -- offer a potentially transformative avenue by which to assess the strategy, choice, and impact of judicial language. Utilizing a corpus of more than one million federal and state appellate court decisions, I estimate word embeddings for the more than 400,000 most common words found in legal opinions. In a series of simple illustrations, I demonstrate the value of this treatment of word meaning for new avenues of law and politics research.

Keywords: Bedeutung, Kontext, Meaning, Rechtswissenschaft, Wortbedeutung
2017
Martiny, Karsten; Möller, Ralf (2017): Reasoning about Imprecise Beliefs in Multi-Agent Systems with PDT Logic. In: KI - Künstliche Intelligenz 31 (1), S. 63-71. DOI: 10.1007/s13218-016-0455-7

DOI: https://doi.org/10.1007/s13218-016-0455-7

Keywords: abductive reasoning, Abduktion, abduktives Schließen, Agenten, Agenten-Überzeugung, Angemessenheit von Überzeugungen, Bedeutung, Belief updates, deutsche Community, Epistemische Logik/Modallogik/Doxastische Logik/Wissenslogik, Formalisierung, frame semantics, imprecise beliefs, Imprecise probabilities, Intellektualtechnik, Knowledge representation, Kogn. Architektur, kognitive Architekturen, Künstliche Intelligenz, Mensch-Technik-Relationen (MTR), model, Modell, Modellierung, multi-agent systems, Multi-Agenten-Systeme, PDT Logic, Probabilistic Doxastic Temporal Logic, Realtechnik, Technik, Ungenaue Überzeugungen, Wahrscheinlichkeit
2015
Fonseca, Andre (2015): Disrupting morphosyntactic and lexical semantic processing has opposite effects on the sample entropy of neural signals. In: BRAIN RESEARCH 1604, S. 1-14

Abstract: Converging evidence in neuroscience suggests that syntax and semantics are dissociable in brain space and time. However, it is possible that partly disjoint cortical networks, operating in successive time frames, still perform similar types of neural computations. To test the alternative hypothesis, we collected EEG data while participants read sentences containing lexical semantic or morphosyntactic anomalies, resulting in N400 and P600 effects, respectively. Next, we reconstructed phase space trajectories from EEG time series, and we measured the complexity of the resulting dynamical orbits using sample entropy an index of the rate at which the system generates or loses information over time. Disrupting morphosyntactic or lexical semantic processing had opposite effects on sample entropy: it increased in the N400 window for semantic anomalies, and it decreased in the P600 window for morphosyntactic anomalies. These findings point to a fundamental divergence in the neural computations supporting meaning and grammar in language. (C) 2015 Elsevier B.V. All rights reserved.

Keywords: Bedeutung, Bedeutung und Grammatik, Bedeutungszusammenhang, frame semantics, Grammar, Grammatiktheorie, Intellektualtechnik, Kogn. Architektur, Kognitionswissenschaft/Social Sciences/Humanities, Kognitive Skills/Social Cognition, lexikalische Semantik, Meaning, Mensch-Technik-Relationen (MTR), Neurowissenschaften, Sprache, Sprachverarbeitung, Sprachverstehen, Technik, Voraussetzungen für sozial angemessenes Verhalten

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