You might want to consider the start of this tutorial.

Short introductions to other TF datasets:

• Dead Sea Scrolls,
• Old Babylonian Letters,

or the

• Q'uran

Trees¶

The textual objects of the BHSA text are syntactic, but they are not syntax trees.

The BHSA is the result of a data-driven parsing strategy with occasional human decisions. It results in functional objects such as sentences, clauses, and phrases, which are build from chunks called sentece-atoms, clause-atoms, and phrase-atoms.

There is no deeper nesting of clauses within phrases, or even clauses within clauses or phrases within phrases. Instead, whenever objects are linguistically nested, there is an edge called mother between the objects in question.

For people that prefer to think in trees, we have unwrapped the mother relationship between clauses and made tree structures out of the data.

The whole generation process of trees, including the quirks underway, is documented in the notebook trees.ipynb. You see it done there for version 2017. We have used an ordinary Python program to generate trees for all versions of the BHSA: alltrees.py

Those trees are available as a feature on sentence nodes, and you can load those features alongside the BHSA data.

Here we show some examples of what you can do with it.

Incantation¶

The ins and outs of installing Text-Fabric, getting the corpus, and initializing a notebook are explained in the start tutorial.

Note that we load the trees module.

We also load the morphology of Open Scriptures for example usage later on.

We first inspect the nature of these features, lets pick the first, last and middle sentence of the Hebrew Bible

We examine feature tree:

Now treen:

The structure of the trees is the same, but treen has numbers between braces in the tags of the nodes. These numbers are the Text-Fabric nodes of the sentences, clauses and phrases that the nodes of the tree correspond to.

Using trees¶

These strings are not very pleasant to the eye. For one thing, we see numbers instead of words. They also seem a bit unwieldy to integrate with the usual text-fabric business. But nothing is farther from the truth.

We show how to

• produce a multiline view
• see the words (in several representations)
• add a gloss
• add morphological data from an other project (Open Scriptures)

Honesty compels us to note that we make use of a bunch of auxiliary functions in an accompanying utils pacckage:

Parsing¶

Key to effective manipulation of tree strings is to parse them into tree structures: lists of lists.

Here we use the generic utility structure():

Apply layout¶

Having the real tree structure in hand, we can layout it in all kinds of ways. We use the generic utility layout() to display it a bit more friendly and to replace the numbers by real Text-Fabric slot numbers:

That opens up the way to get the words in. The third argument of layout() above is str, which is a function that is applied to the slot numbers. It returns those numbers as string, and this is what ends up in the layout.

Fillin the words¶

We can pass any function, why not the function that looks up the word?

Remember that F.g_word_utf8.v is a function that returns the full Hebrew word given a slot node.

Add a gloss¶

Morphology¶

In 2018 I compared the morphology of Open Scriptures with that of the BHSA. See brdiging.

As a by-product I saved their morphology as a Text-Fabric feature on words. So we can add it to our trees.

We also show the nesting depth in the resulting tree.

Taking it further¶

We saw how the fact that we have slot numbers in our tree structures opens up all kinds of possibilities for further processing.

However, so far, we have only made use of slot nodes.

What if we want to draw in side information for the non-terminal nodes?

That is where the feature treen comes in. It has node information for all non-terminals between braces, so it is fairly easy to write new structure() and layout() functions that exploit them.

All steps¶

• start your first step in mastering the bible computationally
• display become an expert in creating pretty displays of your text structures
• search turbo charge your hand-coding with search templates
• exportExcel make tailor-made spreadsheets out of your results
• share draw in other people's data and let them use yours
• export export your dataset as an Emdros database
• annotate annotate plain text by means of other tools and import the annotations as TF features
• map map somebody else's annotations to a new version of the corpus
• volumes work with selected books only
• trees work with the BHSA data as syntax trees

CC-BY Dirk Roorda