The Reading tab comprises a set of contextual sections in support of a first reading of a text. These include bibliographical information about the text (title, author, themes, genres, headnote, references) and a choice between a text view that excludes most paratexts and a document view that represents all of the text in the source edition.
Depending on the form, structure, and content of the text, other available contextual sections include a table of contents, a summative view of the poetic form (metre, stanza form, syllabic pattern, rhyme type and scheme), bibliographic information about the source of the text, a statement of editorial principles applied, any text-specific secondary literature, an introductory essay, other versions of the text in ECPA, related works, and a list of other works by the same author.
ECPA supports the reading process through an extensible contextual reading aid function. When hovering over any word a set of word properties is displayed, including standard spelling, lemma, part of speech, word class, and pronunciation in modern RP according to the International Phonetic Alphabet (IPA). Also identical word tokens and lemmas are highlighted throughout the poem. Additionally, the selected word can be looked up in a number of external dictionaries, thesauri, gazetteers, and reference works.
ECPA makes it easy to add notes or queries to any part of the poetic text by simply clicking on the word or line in question and filling in the annotations form with your details. If the note or query applies not to a word or line, but to an entire stanza or paragraph, or to a piece of paratext, please adjust the context of the annotation settings. Please note that all contributions will be submitted to the editor in the first instance for review. Once peer reviewed, the contribution will be made publicly available under a Creative Commons BY-NC-SA License. This license protects your contributions, but at the same time lets others re-use and build upon them.
We welcome user-contributed content to the Eighteenth-Century Poetry Archive. Throughout the website, you can make contributions to augment an existing piece of information, make a correction to an obvious error (no transcription or edition is without error!), or submit your own notes, glosses, observations, suggestions, readings and interpretations. These contributions help make the resource better for everyone and we thank you for them in advance! These places of peer participation are marked with a icon and are subject to a peer-review process. If you would like to be acknowledged for your contribution, please fill in your contact details in the lower half of the form.
The Analysis tab comprises results from a number of computationally-assisted analytical processes on five core linguistic levels. These analytical layers can be studied individually (hence their containers are collapsible and sortable), when focusing on a particular aspect, for example the relation between verse line and syntax. However they should be considered as connected and interrelated when studying the poem as a whole, as each layer interacts with the others at any given point as well as over time. They require the reader to pay attention to them simultaneously, and to take into account literary as well as sociological features while doing so.
The analysis results thus represent a means of assisting the reader in the task of analysing a poem on a number of interrelated levels. We understand computer-assisted reading as enabling us to realize the full scope of phenomena on phonological, morphological, syntactic, semantic, and pragmatic levels that can be expressed and analysed algorithmically. The key task of fine-tuning the contextual data around every word in a text, i.e. assuming unique significance of every occurrence and its relations to other words, is at the heart of creating the inventory of analytical results. Any of these findings, once verified, are potentially useful, but it is through selection based on relevance and weighting in the context of an individual poem that this potential is fully realized and new insights can be won.
The verse line serves as the basic reference point for all analytical results. Visually as well as rhythmically accentuated, it provides an accessible level of granularity between smaller units such as phonemes, morphemes, and lexemes, and bigger building blocks, such as sentences, stanzas, and ultimately the text as a whole. When hovering over any line the analytical results for that line are dynamically updated on the right. In addition, an integrated view of all analytical layers is displayed when hovering over any word/token (identical words/tokens and lemmas are also highlighted throughout the poem).
As any computationally-assisted analysis of poetic texts that transcends basic quantitative levels is notoriously complex, frequently ambiguous and always error-prone, a word of caution must preface any such undertaking. Despite our best efforts to present useful and interesting results and highlight potential avenues for further investigation, we are aware of the pitfalls and many potential sources of errors, which we will continue to address as ECPA evolves and matures. The main issue of the use of natural language processing (NLP) on language that is both poetic and historically distant can only be addressed through ongoing work to improve domain appropriation, the training of tools on historical corpora, and the contribution of human knowlegde in the form of textual notes, glosses, corrections and queries, interpretations, and models.
The long-term aim of this applied computational criticism is to make it possible, analytically, to "zoom" into a single phoneme, morpheme, lexeme and to seamlessly "zoom" out to the word, the line, the stanza, the whole poem, or even a cluster of poems, thus supplementing the current focus on close reading of individual texts with an analysis of the historical and cultural functions of poetic form on a larger scale. At the functional level, it should be possible to enhance the the website with new tools and let them operate on the underlying texts. Analysis thus becomes an act not separate from, but integrated with the act of reading. The integration of tools with the corpus, rather than as a separate entity, modifies the texts to "research objects".
This layer is concerned with elements traditionally associated with the musical aspects of lyric poems. These include metre, rhythm, rhetorical figures such as alliteration, assonance, and consonance, and, of course, rhyme. In the context of the long tradition of oral transmission of poetry, these patterns of repetition and composition (sonic, rhythmic, or otherwise), contribute to making poems more cohesive and memorizable. More generally, the sound schemata in this layer interact, frequently supporting, countering, or playing with the components of the other layers.
Throughout the 18th century, the dominant prosodic mode is accentual-syllabic, which is based on recurrent units (feet) comprised of any combination of stressed and unstressed syllables in an invariant sequence. This sequence, which is abstracted from the observed combination of stressed and unstressed syllables, is assigned to the poem as its metrical pattern or metre. Distinct from metre, we define realisation, narrowly, as the actual verse pattern of stressed and unstressed syllables (line rhythm) that contrasts or coincides with the metrical pattern.*
The properties highlighted for end rhymes include the rhyme label, the position in the rhyme pattern and stanza type, properties related to stress patterns and across word boundaries, as well as the type(s) of similarity with matching rhymes. Related rhymes are highlighted when hovering over the rhyme words. Some of the global properties of rhyme are summarized in the Poetic Form section in the reading-view.
The rhetorical figures currently detected in the phonological domain are alliteration, paroemion, assonance, and consonance. The components of each figure are highlighted when hovering over the constituent words. Individual patterns of each figure will be highlighted globally when hovering over the identified pattern. Freezing the line currently selected will make it easy to investigate particular sound patterns beyond the confines of the current line, thus highlighting their movement in space and time.
The phonemic display button that switches the Text display between the text of the work and its phonemic transcription in modern RP according to the International Phonetic Alphabet (IPA). Further functionalities, such as highlighting of vowels (short, neutralized, long, diphthong), consonants (plosive, affricate, fricative, nasal, approximant), and vowel and consonant groups, are currently in development.
* As such, realisation must be confused neither with a view that considers metre as variant, nor with a rendition of the line, which can take many different forms depending on the speaker and the historical context. Of course, there is no 1:1 relation between stress and metrical prominence, and a metrical position can be filled by more than one syllable. Realisation is here merely used as a simplified way of recording stress and metrical patterns, but still allows us to highlight interesting phenomena, such as stressed syllables in metrically non-prominent positions etc.
This layer is concerned with the internal structure of words as well as word formation mechanisms. It focuses on the poem as written language, as an act of composition, selecting and arranging morphemes into words and phrases. It examines features such as word formation and choice, syllabic phenomena, composition, and word origins.
Syllables, morphemes, and words are independent units of structure, i.e. there are morphemes that are not syllables, syllables that are not morphemes, words that just consist of a single syllable or morpheme. The number of syllables per line is displayed here and any variations given.
The brief morphological table lists every word in the selected line, giving the word, number of syllables, lemma, word class, part of speech, indication of upper case, word frequency in the poem, and a KWIC list. The plan is to expand the current view to a full morphological analysis in the future.
The rhetorical figures currently detected in the morphological domain are polyptoton, epizeuxis, diacope, anaphora, epistrophe, aphaeresis, apocope, syncope, and synalepha. The components of each figure are highlighted when hovering over the constituent words. Individual patterns of each figure will be highlighted globally when hovering over the identified pattern. Freezing the line currently selected will make it easy to investigate particular morphological patterns beyond the confines of the current line.
This includes the number of words in the text and the number of unique word forms, as well as the resulting vocabulary density. There is also a list of most frequent words in the poem.
This layer is concerned with the analysis of syntactic structures, the position and arrangement of words, interesting phenomena such as parataxis and hypotaxis, and the relationship between verse line, metrical and rhythmic structures, and syntactic units, such as phrases, clauses, and sentences.
The relationship between verse line and syntactic structure is complex and ever changing as the poetic text is played out in time and space. Metrical pattern, rhythm, rhyme, and syntactic structure need to be studied as closely connected and interrelated. The stanza form is an important indicator for further analysis and will be identified first.
A computationally facilitated analysis of the syntactic structure is presented in form of a syntactic dependency parse of the selected sentence. Dependency as a syntactic theory is based on the idea that all linguistic units are connected to each other by directed links named dependencies. A syntactic dependency parse thus connects linguistic units according to their relationships. The result is a tree diagram, to be read from left to right and top to bottom, that serves as a visual representation of syntactic structure, in which the grammatical hierarchy is graphically displayed. The verb is taken to be the structural centre of the clause structure. All other syntactic units are either directly or indirectly connected to the verb in terms of the directed links. Technically spoken, each vertex in the tree represents a lexical unit, child nodes are units that are dependent on the parent, and edges are labelled by the relationship between the words.
The major word classes, nouns, pronouns, verbs, adjectives, and adverbs, are highlighted with a different colour scheme each to make it easier to process the information and to relate it to the verse lines. Hovering over the nodes and edges highlights the node properties as well as the types of dependencies. Closer integration of the syntactic parse with the poetic text is planned for a future update. As a start, a sentencing button has been introduced that highlights syntactic units in the poetic text. The number of sentences in the text and the average number of words per sentence is also displayed.
This layer is concerned with the creation of "literal" meaning on the word and sentence level. The meaning of a sentence is a function of the meaning of its component words (paradigmatic associations) and the way they are combined (syntagmatic associations). The study of the function of this selection and arrangement of words is at the centre of this layer.
For the purpose of a computationally assisted analysis of meaning, frame semantics offers an attractive model as it relativizes word meanings to a finite set of semantic frames. Semantic frames are schematic representations of the conceptual structures and patterns that provide the foundation for meaningful interaction in a given speech community. Thus, semantic frames are linked by linguistic conventions to the meanings of linguistic units (lexical items) constructing a schematic representation of a situation, object, event, or relation and providing the background structure against which words are understood. Each semantic frame identifies a set of frame elements, i.e. participants in the frame (semantic role labels), which in turn are linked to individual lexical units (words). We currently use the SEMAFOR v3.0.4 alpha [pre-trained] software to generate the frame semantic parses and the frameviz.js software to visualize them.
Just like the syntactic dependency parse, the frame semantic parse is meant to be read from left to right and top to bottom. At the top are the lexical units of the selected sentence. Below the lexical units are the names of the evoked frames, a complete list of which can be found at FrameNet. The subsequent rows indicate the frame elements for each frame. Frame element spans are indicated with blue bars. For the future, the plan is both to adapt the frames for the narrower context of eighteenth-century writing by supplementing the frame associations with historical contextual information, such as contemporary dictionaries and historical gazetteers, and to integrate the results of this analysis more closely with the other analytical layers.
NB: Meaning is notoriously difficult to establish computationally, and the analysis presented here should be considered experimental. Frames may be evoked erroneously when lexical units are not or wrongly mapped to frame elements due to changes in word meaning, a loss of meaning altogether, or a change of associations conveyed through historical distance between speaker and recipient, or insufficient domain appropriation.
The rhetorical figures currently detected in the semantic domain are similie and homophonic paronomasia. The components of each figure are highlighted when hovering over the constituent words. Individual patterns of each figure will be highlighted globally when hovering over the identified pattern. Please be aware that semantic figures of speech are complex entities and provide a considerable challenge for computationally facilitated detection.
Unlike semantics, which is concerned with the creation of meaning on the level of the word and sentence, this layer is concerned with the creation of meaning in context. The poem is considered as spoken language, i.e. as an act of internal communication between speaker and addressee in the text, and external communication between the poet and the reader and in a wider sense with society itself. This layer comprises elements such as discourse, intention, argumentative structure, internal and external contexts, themes and genre, and real-world references (e.g. named entities).
The rhetorical figures currently detected in the pragmatic domain are ecphonesis, apostrophe, and pysma. The components of each figure are highlighted when hovering over the constituent parts. Individual patterns of each figure will be highlighted globally when hovering over the identified pattern.
Among the various types of referring expressions, references to named entities are crucial to the communication process in a specific context. For the purpose of identifying these references to named entities, ECPA uses a hand-curated and domain customized gazetteer that has been constructed from the results of four NERC engines (Morphadorner, Stanford NER, MITIE, and OpenNLP). We have supplemented the gazetteer with automated PoS-based named entity recognition (classifier), and the source of the detected named entity will be identified from one of these two sources.
As an enabling technology, Named Entity Recognition and Classification is often a pre-processing step for relation extraction, knowledge base generation (taxonomies, ontologies, thesauri), question answering, semantic search, and proper noun and pronominal coreference resolution. All of these areas may offer valuable avenues of enquiry in future updates.
The Visualization tab comprises a set of original and adapted visualizations intended to support the analysis/interpretation of the poems in the Eighteenth-Century Poetry Archive. By shedding light on the texts from different visualization perspectives (presentational/disseminative, operational/observational, analytical/interactive, creative/inventive) and with varying foci on one or more analytical layers, the visualizations serve as a toolbox for researchers interested in visual interpretation.
The Visualization home page will list and briefly introduce (i.e. provide information about the visualization perspectives and analytical foci of) all visualizations available for the chosen poem. You can return to this home page at any time by following the Visualization Home-link, which can be found near the top left corner in all visualizations. When first accessing the visualization tab, the evenly split layout of the workspace will be changed slightly in favour of the visualization space; the text of the poem will, however, remain visible at all times.1
The list of available visualizations for the poem under consideration is generated automatically. Some visualizations will not be available for prose poems, or will have a limited number of display options.2 You can learn more about the chosen visualization by clicking on the help-symbol () behind the visualization's logo in the top left corner. As new visualizations are added over time, the list will ultimately cover all analytical layers and will offer a variety of visualization perspectives. Please do contact the editor with suggestions for additional visualizations or feedback about the usability and usefulness of the visualizations offered. Thank you!
1 The vertical divider can be dragged to adjust the layout to
suit individual preference.
2 Please also be advised that some visualizations can be slow to render when the number of lines in the poem exceeds a few hundred.
Phonemia visualizes the phonemic makeup of a poem (in modern RP). It visualizes vowel and consonant groups and distributions using easy-to-read colour highlighting. It draws attention to sonic patterns, points of contact and opposition, hotspots, and the use of sound devices for particular effects. Phonemia stands in a long tradition of quantitative as well as qualitative studies of the phonemic composition of poems.1
Phonemia is comprised of three2 related displays, which are intended to support shifting perspectives as the exploratory close reading process evolves over time. At the centre of all displays is a complete phonemic transcription of the whole poem (or of a subsection at a time).
- Phonemic transcription / distribution: The distribution display presents a tabular overview of the distribution of vowel and consonant groups in each line of the poem. Each of the phonemic units can be selected invividually in the control panel on the left. This panel also lists vowels, consonants, and all phonemes sorted by frequency. In addition, sonic devices such as alliteration or end rhymes are highlighted (sound devices are visualized in both the poetic text and its phonemic transcription).
- Phonemic transcription / metre: Phonemia's second display focuses on the metrical and rhythmic qualities of the poem, by presenting a complete scansion of the poem. A metrical and a syllable pattern are assigned manually to every poem as part of the editorial process in ECPA and this pattern is visualized in the scansion result. When differences in the syllabic/metrical pattern and realization cannot be resolved, we employ the ZeuScansion tool, to suggest a scansion. Based on the quality of the available evidence, a confidence rating is assigned to each scanned line.
- Phonemic transcription / word classes: The word classes display visualizes the relation of parts of speech to phonological properties. It acknowledges the role word classes play when considering phonemic properties, including but not limited to varieties of stress, rhythmic qualities, word and syllable lengths, and voicing. The study of the distribution of word classes, their co-occurrence, and the significance of their verse and sentence positions can be augmented by this display.
Phonemia highlights not only the repetition of certain phonemes in close proximity, but also of groups of phonemes that share a number of features and can thus produce an accumulative effect. To make these more transparent, a warm colour scheme has been chosen for vowel groups and a cold colour scheme has been applied to consonant groups. The effectiveness of these choices is subject to review and may change if feedback suggests other more appropriate visual representations.
Future work may include supplementing modern RP with the phonology of eighteenth-century English, evidence of which can be found in numerous pronunciation dictionaries produced in the later eighteenth century. One of them, Thomas Spence's Grand Repository of the English Language (1775), contains a detailed phonetic script illustrating "correct" pronunciation.3
1 An early example of phonemic analysis is James J. Lynch's "The Tonality of Lyric Poetry: An Experiment in Method", Word 9(3) (1953): 211-224. Phonemia's distribution display is indebted to Marc R. Plamondon's English Poetic Phonemics-project (2008/9).
2 Only the word classes display is available for prose poems.
3 See Joan Beal, English Pronunciation in the Eighteenth Century: Thomas Spence's 'Grand Repository of the English Language', Oxford: OUP, 1999. See also Charles Jones, English Pronunciation in the Eighteenth and Nineteenth Centuries, Houndmills: Palgrave Macmillan, 2006.
- 0:00 Project introduction and participants
- 0:26 Close reading context
- 2:24 Poetic variables
- 3:31 Rule-based visual mappings
- 5:34 Visualization design
- 6:36 Visualization interface
- Comparing Three Designs of Macro-Glyphs for Poetry Visualization. A. Abdul-Rahman, E. Maguire, and M. Chen. In Proceedings of EuroVis 2014, Short Paper, 2014. [DOI]
- Rule-based Visual Mappings — with a Case Study on Poetry Visualization. A. Abdul-Rahman, J. Lein, K. Coles, E. Maguire, M. Meyer, M. Wynne, C. R. Johnson, A. Trefethen, and M. Chen. In Computer Graphics Forum 32(3) (2013): 381-390. (Presented in EuroVis 2013.) [DOI]
- Freedom and Flow: A New Approach to Visualizing Poetry. A. Abdul-Rahman, K. Coles, J. Lein and M. Wynne. In Digital Humanities 2013, Lincoln, Nebraska, 2013. [Abstract]
This re-implementation of Double Tree includes several of the enhancements mentioned in Culy and Lyding, 2010, including the abilities to sort the branches by a variety of properties, to filter the branches by different properties, and to search the words in the Double Tree. It also is designed to work with various types of structured data.
DoubleTreeJS is © 2012-2016, Chris Culy. Used under a BSD license.
- Culy, C., M. Passarotti, and U. König-Cardanobile. 2014. "A Compact Interactive Visualization of Dependency Treebank Query Results". Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), Rejkjavik, Iceland. May 26-31, 2014. N. Calzolari et al. (eds.). ELRA.
- Culy, C. and V. Lyding. 2010. "Double Tree: An Advanced KWIC Visualization for Expert Users". Information Visualization, Proceedings of IV 2010, 2010 14th International Conference Information Visualization, 98-103.