Text-Fabric

A corpus of ancient texts and (linguistic) annotations represents a large body of knowledge. Text-Fabric (TF) makes that knowledge accessible to programmers and non-programmers.

TF is machinery for processing such corpora as annotated graphs. It treats corpora and annotations as data, much like big tables, but without losing the rich structure of text, such as embedding and multiple representations. It deals with text in a state where all markup is gone, but where the complete logical structure still sits in the data.

Whether a corpus comes from plain texts, OCR output, databases, XML, TEI: TF has support to convert it to single column files, where each file corresponds with a feature of the text.

The Python library tf can be used to collect a bunch of features and display it as an annotated text. What ties the features together are natural numbers, that serve to anchor the elementary positions in the text as well as the relevant structures within the text.

When TF loads a dataset of features, you can instruct it to get the features from anywhere. That means it supports workflows where annotations are produced by third parties and can be used against the original corpus, without additional work. It also facilitates mappings between ongoing versions of the corpus, so that annotations made on older versions can be ported to newer versions without redoing the annotation creation.

Straight to …

• Release notes (tf.about.releases)
• Install (tf.about.install)
• FAQ (tf.about.faq)
• Corpora (tf.about.corpora)
• Browser (tf.about.browser)
• Search Client (tf.about.clientmanual) simplified (tf.about.manual)
• Use (tf.about.use)
• Search (tf.about.searchusage)
• Volumes and collections (tf.about.volumes)
• API (tf.cheatsheet)
• Annotation, manual (tf.about.annotate)
• Data sharing (tf.about.datasharing)
• Data Structures and Algorithms (tf.about.datamodel, tf.about.searchdesign, tf.about.displaydesign)
• File Format (tf.about.fileformats, tf.about.optimizations)
• Converting to TF (tf.convert.walker, tf.convert.mql)
• Exporting data and re-importing it with enrichments (tf.convert.recorder)
• Dataset manipulation (tf.dataset.modify and Versions)
• Crossing versions of datasets (tf.dataset.nodemaps)
• Code Organization (tf.about.code)

Author

Author: Dirk Roorda

Cite TF as DOI: 10.5281/zenodo.592193.

Acknowledgments

TF is a matter of putting a few good ideas by others into practice.

While I wrote most of the code, a product like TF is unthinkable without the contributions of avid users that take the trouble to give feedback and file issues, and have the zeal and stamina to hold on when things are frustrating and bugs overwhelming, and give encouragement when they are happy.

In particular thanks to

• Cale Johnson
• Camil Staps
• Christian Højgaard-Jensen
• Christiaan Erwich
• Cody Kingham
• Ernst Boogert
• Eliran Wong
• Gyusang Jin
• James Cuénod
• Johan de Joode
• Kyoungsik Kim
• Martijn Naaijer
• Oliver Glanz
• Stephen Ku
• Willem van Peursen

2022-now

2014-2022

Special thanks to Henk Harmsen for nudging me into a corner where I was exposed to the Hebrew Text Database, and for letting me play there for almost longer than could be defended.

And to Andrea Scharnhorst for understanding and encouragement on this path.

More resources

Tutorials:

• BHSA
• DSS
• OldBabylonian
• OldAssyrian
• Uruk
• Quran
• and more via tf.about.corpora.

Papers:

• Coding the Hebrew Bible
• Parallel Texts in the Hebrew Bible, New Methods and Visualizations
• The Hebrew Bible as Data: Laboratory - Sharing - Experiences (preprint: arxiv)
• LAF-Fabric: a data analysis tool for Linguistic Annotation Framework with an application to the Hebrew Bible
• Annotation as a New Paradigm in Research Archiving

Presentations:

Hands on with Dead Sea Scrolls, Old Babylonian Tablets, and the Quran (Lorentz Leiden 2020)

Text-Fabric in Context (Lorentz Leiden 2020)

Data Analysis in Ancient Corpora (Cambridge 2019, with Cody Kingham)

Text-Fabric as IKEA logistics (Copenhagen 2017)

Here is a motivational presentation, given just before SBL 2016 in the Lutheran Church of San Antonio.

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Sub-modules

tf.about

Documents …

tf.advanced

Advanced API …

tf.app

Make use of a corpus …

tf.browser

Local TF data and web server

tf.capable

Dependency management …

tf.cheatsheet

A. Advanced API …

tf.clean

Clean …

tf.client

Layered Search …

tf.convert

Various forms of data interchange …

tf.core

Core API of TF …

tf.dataset

Dataset operations …

tf.fabric

Fabric …

tf.lib

Utility functions …

tf.parameters

Parameters …

tf.search

Guidance for searching …

tf.tools

Various tools for workflows around TF.

tf.volumes

Volume operations …

tf.writing

Writing systems support …

tf.zip