Sensing Ambiguity in Henry James' "The Turn of the Screw (original) (raw)
Related papers
Haunted by ambiguities' revisited: in search of a metamethod for literary text disambiguation
Lege Artis
This paper addresses the issue of ambiguity in literary discourse, viewed through its multiple verbal and narrative manifestations in Virginia Woolf's short fiction. The research is aimed to combine traditional and most recent techniques of semantic, conceptual, narrative, semiotic, and configurational analyses as constituents of a metamethod of literary text disambiguation, which highlights some hidden features of the writer's linguistic personality.
A Tale of Two Cultures: Bringing Literary Analysis and Computational Linguistics Together
2013
There are cultural barriers to collaborative effort between literary scholars and computational linguists. In this work, we discuss some of these problems in the context of our ongoing research project, an exploration of free indirect discourse in Virginia Woolf’s To The Lighthouse, ultimately arguing that the advantages of taking each field out of its “comfort zone” justifies the inherent difficulties.
Proceedings of the Fourth Workshop on Computational Linguistics for Literature
2015
Welcome to the 4 th edition of the Workshop on Computational Linguistics for Literature. After the rounds in Montréal, Atlanta and Göteborg, we are pleased to see both the familiar and the new faces in Denver. We are eager to hear what our invited speakers will tell us. Nick Montfort, a poet and a pioneer of digital arts and poetry, will open the day with a talk on the use of programming to foster exploration and fresh insights in the humanities. He suggests a new paradigm useful for people with little or no programming experience. Matthew Jockers's work on macro-analysis of literature is well known and widely cited. He has published extensively on using digital analysis to view literature diachronically. Matthew will talk about his recent work on modelling the shape of stories via sentiment analysis. This year's workshop will feature six regular talks and eight posters. If our past experience is any indication, we can expect a lively poster session. The topics of the 14 accepted papers are diverse and exciting. Once again, there is a lot of interest in the computational analysis of poetry. Rodolfo Delmonte will present and demo SPARSAR, a system which analyzes and visualizes poems. Borja Navarro-Colorado will talk about his work on analyzing shape and meaning in the 16 th and 17 th century Spanish sonnets. Nina McCurdy, Vivek Srikumar & Miriah Meyer propose a formalism for analyzing sonic devices in poetry and describe an open-source implementation. This year's workshop will witness a lot of work on parallel texts and on machine translation of literary data. Laurent Besacier & Lane Schwartz describe preliminary experiments with MT for the translation of literature. In a similar vein, Antonio Toral & Andy Way explore MT on literary data but between related languages. Fabienne Cap, Ina Rösiger & Jonas Kuhn explore how parallel editions of the same work can be used for literary analysis. Olga Scrivner & Sandra Kübler also look at parallel editionsin dealing with historical texts. Several other papers cover various aspects of literary analysis through computation. Prashant Jayannavar, Apoorv Agarwal, Melody Ju & Owen Rambow consider social network analysis for the validation of literary theories. Andreas van Cranenburgh & Corina Koolen investigate what distinguishes literary novels from less literary ones. Dimitrios Kokkinakis, Ann Ighe & Mats Malm use computational analysis and leverage literature as a historical corpus in order to study typical vocations of women in the 19 th century Sweden. Markus Krug, Frank Puppe, Fotis Jannidis, Luisa Macharowsky, Isabella Reger & Lukas Weimar describe a coreference resolution system designed specifically with fiction in mind. Stefan Evert, Thomas Proisl, Thorsten Vitt, Christof Schöch, Fotis Jannidis & Steffen Pielström explain the success of Burrows's Delta in literary authorship attribution. Last but not least, there are papers which do not fit into any other bucket. Marie Dubremetz & Joakim Nivre will tell us about automatic detection of a rare but elegant rhetorical device called chiasmus. Julian Brooke, Adam Hammond & Graeme Hirst describe a tool much needed in the community: GutenTag, a system for accessing Project Gutenberg as a corpus. iii To be sure, there will be much to listen to, learn from and discuss for everybody with the slightest interest in either NLP or literature. We cannot wait for June 4 (-:). This workshop would not have been possible without the hard work of our program committee. Many people on the PC have been with us from the beginning. Everyone offers in-depth, knowledgeable advice to both the authors and the organizers. Many thanks to you all! We would also like to acknowledge the generous support of the National Science Foundation (grant No. 1523285), which has allowed us to invite such interesting speakers.
Computation and Interpretation in Literary Studies
Critical Inquiry, 2021
The article suggests that the best examples of textual work in the computational humanities are best understood as motivated by aesthetic concerns with the constraints placed on literature by computation’s cultural hegemony. To draw these concerns out, I adopt a middle-distant depth of field, examining the strange epistemology and unexpected aesthetic dimension of numerical culture’s encounters with literature. The middle-distant forms of reading I examine register problematically as literary scholarship not because they lack rigor or evidence but because their unacknowledged object of study is the infrastructure of academic knowledge production. Work in the computational humanities is approaching a point at which the scale of analyzed data and data analysis washes out readings, the algorithms are achieving opaque complexity, and the analytical systems are producing purposive outputs. These problems cannot be addressed without attending to the aesthetics of data-driven cultural encounters, specifically the questions of how we produce readings/viewings and how they change our perceptions and characterize the interesting, critical theorization on method and meaning that make the best work in the computational humanities legitimately humanistic. I contribute a working example: a recommendation system for passages within the Shakespearean dramatic corpus, built using a large bibliographical dataset from JSTOR, a counting/ranking algorithm used at large scale. The system returns passages as intertexts for the passage a reader has selected. I explain how and why this system provides meaningful intertextual connections within the Shakespearean dramatic corpus by tracing the legible structural effects of disciplinary knowledge formation on the shape of this dataset. I close by suggesting how the computational and more traditional methods in the humanities might begin to stop debating past one another.
UNDERSTANDING AND EXPLAINING THE LITERARY TEXT: A RETURN TO INTERPRETATION
I would like to take the opportunity of our present theme, 'Old Challenges / New Horizons', not to report on any very particular aspect of my own research, but to offer some thoughts on issues which seem to me important for the nature and future of English literature as a discipline, on the basis of my experience as a scholar and teacher of English literature in the English university environment. Some of my observations and concerns no doubt relate specifically to the United Kingdom, and they might at least satisfy some of the curiosities you may have about the odd ways in which we British do things. Some of my observations however may have larger and European resonances. I speak as one who professes the discipline of English literature, but I shall be exploring areas where language studies have much to offer, and where the cooperation of literary and language expertise might well, it seems to me, be profitably explored. I am a scholar of the long eighteenth century, and both a practising and a theorising textual editor, and many of my examples, but not all, come from that period and that field. We are all of us familiar with the notion that English literature is chronically a discipline in crisis. In some ways that might seem an odd notion. The subject remains, throughout the world, intellectually vibrant and productive, and recruits well in a competitive world. Nevertheless, English literature has surely experienced, over the last three decades, a greater degree of internal methodological contest than any other. Self-examination is healthy; nosce teipsum. A continuous and unremitting state of self-questioning however has led, many believe, to a radical loss of disciplinary confidence and identity. The theory explosion of the seventies and eighties deconstructed many old certainties about texts and their understanding. The hermeneutics of suspicion have led many to read texts not for what they say, but for what they allegedly conceal. The notions that texts might be read for their avowed meanings, or that authorial intention might be a credible voucher of meaning, or that meanings might be in any sense determinable, fractured under these pressures. In a field of English literary studies in which I have a strong personal investment, textual editing and explanatory annotation, many theorists argued that not only the meaning of words, but the printed texts in which they appeared, were radically unstable. In the extreme case some theorists went on to assert that any pretence not only to credible textual editing, but to any kind of credible textual interpretation or explanation, or indeed to English itself
2017
Text reuse is a common way to transfer historical texts. It refers to the repetition of text in a new context and ranges from nearverbatim (literal) and para-phrasal reuse to completely non-literal reuse (e.g., allusions or translations). To improve the detection of reuse in historical texts, we need to better understand its characteristics. In this work, we investigate the relationship between para-phrasal reuse and word senses. Specifically, we investigate the conjecture that words with ambiguous word senses are less prone to replacement in para-phrasal text reuse. Our corpus comprises three historical English Bibles, one of which has previously been annotated with word senses. We perform an automated wordsense disambiguation based on supervised learning. By investigating our conjecture we strive to understand whether unambiguous words are rather used for word replacements when a text reuse happens, and consequently, could serve as a discriminating feature for reuse detection.
Literary and Linguistic Computing, Vol. 18, No. 4 ALLC 2003; all rights reserved 423
2007
Large, real world, data sets have been investigated in the context of Authorship Attribution of real world documents. Ngram measures can be used to accurately assign authorship for long documents such as novels. A number of 5 (authors) # 5 (movies) arrays of movie reviews were acquired from the Internet Movie Database. Both ngram and naive Bayes classifiers were used to classify along both the authorship and topic (movie) axes. Both approaches yielded similar results, and authorship was as accurately detected, or more accurately detected, than topic. Part of speech tagging and function-word lists were used to investigate the influence of structure on classification tasks on documents with meaning removed but grammatical structure intact.
Automatic Ambiguity Resolution in Natural Language, Alexander Franz
1999
During the last ten years, corpus-based approaches to natural language processing (NLP) have received a lot of attention, resulting in extensive ongoing work in statistical methods in Computational Linguistics. Corpus-based linguistics focuses on language data, for instance as available through large text corpora, whereas approaches in the Chomskian tradition try to give an abstract model of grammatical competence. It is not uncommon in the latter approach to focus on natural language examples that sometimes appear to be rare and hard to judge as grammatical or ungrammatical. Corpus-based linguistics, on the other hand, examines examples that were actually expressed in a spoken or written way. This change in perspective leads to a totally different set of problems and a different methodology to solve them. Often it is difficult for traditional and corpus-based linguists to understand the problems of the other, and it appears to be very hard to work out a unified approach to solve the difficulties in natural language processing. This situation is nicely exemplified by Franz' book.