New Feature: Discourse Datasets and Visual Filters (Dataset)

Jacob Cerone
Jacob Cerone Member, Logos Employee Posts: 293
edited November 2024 in English Forum

What is it?

Logos' Discourse Datasets and Visual Filters represent the culmination of years of study on discourse features and devices, which speakers and writers of all languages use to convey meaning. The datasets and visual filters constitute a complete discourse analysis of the whole Bible, constructed with graphical representations for numerous communicative devices throughout the Hebrew Old Testament and Greek New Testament. The datasets are searchable, so you can find every occurrence of direct address in the Old or New Testaments. And with the use of our reverse interlinear data, you can use the Discourse features visual filters to view these annotations in several different English, Greek, or Hebrew bibles.

How does it work?

Open any of your Bibles with a reverse interlinear. Navigate to the visual filters icon. From here, you can enable the Discourse Features (Greek) or Discourse Features (Hebrew) visual filters as a whole, or you can individually select the feature you want exposed in your English translation (or Greek and Hebrew texts).*

You can also search the dataset. The syntax for this search for the Greek dataset is <LDGNT = Overspecification> in the basic search. To search the Hebrew dataset use <LDHB = Overspecification>.

The easiest way to search this dataset, however, is to have the visual filters enabled, locate the feature you want to investigate further, right click on any of the words tagged with the feature you're investigating, and select that option from the context menu to search. Logos will automatically generate the search syntax for you.

* Please note that the discourse dataset was developed for the NA28 and the SBLGNT. Accordingly, if you enable the visual filters on a Byzantine Greek text or translation heavily dependent on the Byzantine textual tradition (e.g. KJV), there may be significant discrepancies between the data within this dataset and the text itself. 

Where can I learn more?

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