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Code and Tutorial Accompanying "Computer-Assisted Language Comparison: State of the Art" ...
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Code and data accompanying the study "Modeling word trees in historical linguistics" ...
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Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels ...
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The Quest for 'Falsehood', or a Survey of Tools for the Study of Greek-Syriac-Arabic Translations ...
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Towards Olfactory Information Extraction from Text: A Case Study on Detecting Smell Experiences in Novels ...
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The Quest for 'Falsehood', or a Survey of Tools for the Study of Greek-Syriac-Arabic Translations ...
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Towards Programming in Natural Language: Learning New Functions from Spoken Utterances ...
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Модели и методы анализа тональности в текстах на башкирском языке ... : Models and methods for sentiment analysis of texts in Bashkir language ...
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Imiona w Polsce w XX w. i na początku XXI w. w ujęciu statystycznym i socjolingwistycznym ...
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Imiona w Polsce w XX w. i na początku XXI w. w ujęciu statystycznym i socjolingwistycznym ...
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Pathways to the Native Storyteller: a method to enable computational story understanding
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In: College of Computing and Digital Media Dissertations (2020)
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THE FUTURE TENSE PROPERTIES of UYGHUR and TURKISH
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In: Zeitschrift für die Welt der Türken / Journal of World of Turks; Vol 12, No 2 (2020): [ZFWT] VOL. 12, NO. 2 (2020); 69-80 (2020)
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A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics
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In: Computer Science: Faculty Publications and Other Works (2020)
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Discovering and analysing lexical variation in social media text ...
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Speaker trait characterization in web videos: Uniting speech, language, and facial features
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In: Proceedings of the 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013) ; 3647-3651 ; International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013) ; 38 (2020)
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Distant Reading in der Zeitgeschichte: Möglichkeiten und Grenzen einer computergestützten Historischen Semantik am Beispiel der DDR-Presse
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In: Zeithistorische Forschungen / Studies in Contemporary History ; 16 ; 1 ; 177-196 (2020)
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Urban Narrative: Computational Linguistic Interpretation of Large Format Public Participation for Urban Infrastructure
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In: Urban Planning ; 5 ; 4 ; 20-32 ; The City of Digital Social Innovators (2020)
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A Corpus Approach to Roman Law Based on Justinian’s Digest
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Abstract:
Traditional philological methods in Roman legal scholarship such as close reading and strict juristic reasoning have analysed law in extraordinary detail. Such methods, however, have paid less attention to the empirical characteristics of legal texts and occasionally projected an abstract framework onto the sources. The paper presents a series of computer-assisted methods to open new frontiers of inquiry. Using a Python coding environment, we have built a relational database of the Latin text of the Digest, a historical sourcebook of Roman law compiled under the order of Emperor Justinian in 533 CE. Subsequently, we investigated the structure of Roman law by automatically clustering the sections of the Digest according to their linguistic profile. Finally, we explored the characteristics of Roman legal language according to the principles and methods of computational distributional semantics. Our research has discovered an empirical structure of Roman law which arises from the sources themselves and complements the dominant scholarly assumption that Roman law rests on abstract structures. By building and comparing Latin word embeddings models, we were also able to detect a semantic split in words with general and legal sense. These investigations point to a practical focus in Roman law which is consistent with the view that ancient law schools were more interested in training lawyers for practice rather than in philosophical neatness.
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Keyword:
clustering; computational linguistics; corpus linguistics; Digest; distributional semantics; Latin; LatinISE; Python; Roman law; word embeddings
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URL: https://www.repository.cam.ac.uk/handle/1810/311633 https://doi.org/10.17863/CAM.58723
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