Lists enables students and instructors to generate customized vocabulary lists from its database of Greek and Latin textbooks and texts. A list might include all the vocabulary from a core list, an ancient text, or a textbook. But users can focus on a selection of a list or work and also customize their lists to take into account textbooks that they have used, core lists they have mastered, and texts they have already read. They can also create lists of words that appear in their text and other texts that have read or might read. These lists can then be sorted, searched, and filtered to focus on one or more parts of speech, among other options, and then printed or downloaded in a variety of formats.
Bridge/Lists was first developed by Julie Ta (Haverford '16) and Blair Rush ('16) in the summer of 2014. Significant revisions were begun in the summer and fall of 2015 by Jack Raisel ('17) and Julie Ta; subsequent improvements were made by Byron Biney (Swarthmore '19), Dylan Emery (Haverford '19), and Aleena Maryam (‘21). The current version of the Bridge was developed in 2020 by Carter Langen ('22) using a new UI protoyped by Fiona Xu ‘21, Samuel Tan ‘23.
Lemmatizer creates a lemmatization spreadsheet for a Latin or Greek text. You can choose to either upload a text file, or just input text yourself. We will lemmatize all the words that have only one possible lemma, and will return a csv that is almost ready to import. All you have to do is identify the lemmata for the remaining words (usually around 40% of an average text) and then you will have a text ready to analyze — or import into the Bridge!
Bridge/Lemmatizer was created by Jack Raisel ('17) and James Faville ('19), with the web version designed by Fatima Noor ('21). The current version was launched 2020 by Carter Langen ('22). A successor app, Lemmatizer2 will fold the app into a fully web-based environment, allowing more rapid, accurate, and detailed lexical and syntactic encoding of Latin texts, and facilitating collaboration by faculty, students, and other contributors; anticipated launch 2022.
Oracle will allow you to discover readable texts in The Bridge Corpus by revealing the authors, texts, and passages that have the highest percentage of familiar vocabulary. Select the textbooks you’ve used, lists you’ve mastered, and texts that you’ve read. Then let Bridge/Oracle reveal your next text(s).
Developed by Carter Langen ('22) and launched in 2020.
Stats will be a web-based dashboard that displays information about lexical and syntactic difficulty — i.e., readability — for one or more texts, and the effect that user-defined knowledge has on textual readability. TATS will use the data in the Bridge ecosystem (including new data generated via Lemmatizer2) to derive standard measures of readability: e.g., (1) word length; (2) word frequency or the prevalence of very common words; (3) lexical sophistication or the percentage of words that provide more precise and more nuanced meanings; (4) lexical density or the ratio of content words to function words; (5) lexical variation or the variety of different words; and (6) hapax legomenon or words that appear only once. It will also analyze syntactic measures such as: the (1) number words per sentence; (2) the length of sentences and (3) the number and length of subordinate clauses. From these data STATS will provide standard readability scores (e.g., LIX, RIX, ARI, Coleman Liau Index, Modified Dale-Chall, Coh-Matrix, etc.) and scores tailored to Latin (e.g., LexR). These analyses can be shared, saved to a Bridge user account, or exported for archiving or additional investigation.
Currently in development; anticipated launch 2021.
Syllabus will be a web-based tool that will enable instructors to design and manage data-informed lesson plans, syllabi, and curricula by discovering texts that demonstrate vocabulary and grammar in context, and optimize the sequence of texts to promote durable acquisition of lexical and syntactical knowledge. SYLLABUS will reveal comprehensible texts that demonstrate known vocabulary and/or grammar in context. Users will select and/or allow SYLLABUS to reveal the most comprehensible or relevant texts based on a set of search parameters (e.g., lexical familiarity, closest readability scores, presence of key vocabulary or targeted syntax). They can then (re)order the texts — or allow the tool to sequence texts — to optimize progress towards course goals by, for example, prioritizing vocabulary building, extensive reading, or incrementally increasing the reading difficulty of the texts. SYLLABUS will display key data for the texts and the tested sequence(s), allowing instructors to be more intentional about their text selections. These analyses can be shared, saved to a Bridge user account, or exported for archiving or additional investigation. Texts and words identified through SYLLABUS will be integrated with Bridge/Lists to create customized vocabulary resources.
Currently in development; anticipated launch 2023.
Bridge/Scribe will markup a text to reveal familiar and/or new vocabulary.
For example, if you used the Bridge to create a list of new vocabulary in the first sentence of Caesar's Bellum Gallicum excluding the words in the DCC Latin Core, you would see: Gallia est omnis divisa in partes tres, quarum unam incolunt Belgae, aliam Aquitani, tertiam qui ipsorum lingua Celtae, nostra Galli appellantur.
Currently in development; anticipated launch 2024.
To make a suggestion or to inquire about contributing to the project, please contact us.