Notebook

Loading Text-Fabric (Nestle1904LFT)¶

Work in progress!

Table of content ¶

1 - Introduction
- 1.1 - Text-Fabric data versions
2 - Preparation / installation
3 - Load Text-Fabric into memory
- 3.1 - Load the code
- 3.2 - Load the app and data
4 - Add additional features
5 - Using multiple Text-Fabric corpora

1 - Introduction ¶

Basic instructions on loading the Text-Fabric and start using it on your system. It will provide examples of the various ways you can invoke Text-Fabric.

1.1 - Text-Fabric data versions ¶

Some discussion related to versions

2 - Preparation / installation ¶

back to TOC ¶

The instructions in this section are only required once to be executed. This will result in the Text-Fabric code being available for loading into memory of your system.

2.1 - Install Python ¶

You need to have Python on your system. Most systems have it out of the box,but alas, that is python2 and we need at least python 3.6.

Install it from python.org or from Anaconda.

2.2 - Install Text-Fabric ¶

(if not yet installed)

TF itself

pip3 install text-fabric

When using Jupyter notebook

You can install Jupyter Notebook by command:

pip3 install jupyter

When using Anaconda

A platform like Anaconda allows for easy installation of Jupyter.

It is advisable to define a new environment in Anaconda on which Text-Fabric can be installed (documentation).

2.3 - Raise rate limit on Github ¶

back to TOC ¶

It may be required to increase rate limit for GitHub. See instructions on aquiring and setting the GHPERS variable. See here if you want to set the varibale on windows using the command prompt.

3 - Load Text-Fabric into memory ¶

back to TOC ¶

The instructions in this section are required once to be executed each time you want to use Text_Fabric. It will load the Text-Fabric code and data into memory.

3.1 - Load the code ¶

back to TOC ¶

In [1]:

%load_ext autoreload
%autoreload 2

In [1]:

# Loading the Text-Fabric code
# Note: it is assumed Text-Fabric is installed in your environment
from tf.fabric import Fabric
from tf.app import use

3.2 - Load app and data ¶

The following invocation of function use loads all features of the corpus (and extra modules, see section 4). It creates an variable (in this example N1904LFT) with its associated methods and function, the 'Advanced API'. In the 'cheat sheet' there are many references to A.*something*. In this notebook they should be read as N1904LFT.

In [7]:

# load the app and data
N1904LFT = use ("tonyjurg/Nestle1904LFT", version="0.6", hoist=globals())

Locating corpus resources ...

The requested app is not available offline
	~/text-fabric-data/github/tonyjurg/Nestle1904LFT/app not found

Status: latest release online v0.6a versus None locally

downloading app, main data and requested additions ...

app: ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/app

The requested data is not available offline
	~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6 not found

Status: latest release online v0.6a versus None locally

downloading app, main data and requested additions ...

data: ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6

   |     0.19s T otype                from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     2.50s T oslots               from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.46s T verse                from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.61s T word                 from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.51s T after                from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.60s T wordtranslit         from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.50s T chapter              from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.62s T normalized           from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.61s T unicode              from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.57s T book                 from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.60s T wordunacc            from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |      |     0.06s C __levels__           from otype, oslots, otext
   |      |     1.82s C __order__            from otype, oslots, __levels__
   |      |     0.07s C __rank__             from otype, __order__
   |      |     3.26s C __levUp__            from otype, oslots, __rank__
   |      |     1.93s C __levDown__          from otype, __levUp__, __rank__
   |      |     0.22s C __characters__       from otext
   |      |     0.95s C __boundary__         from otype, oslots, __rank__
   |      |     0.04s C __sections__         from otype, oslots, otext, __levUp__, __levels__, book, chapter, verse
   |      |     0.23s C __structure__        from otype, oslots, otext, __rank__, __levUp__, book, chapter, verse
   |     0.45s T booknumber           from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.51s T bookshort            from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.48s T case                 from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.33s T clausetype           from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.58s T containedclause      from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.42s T degree               from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.58s T gloss                from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.49s T gn                   from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.03s T headverse            from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.33s T junction             from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.60s T lemma                from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.56s T lex_dom              from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.58s T ln                   from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.42s T markafter            from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.43s T markbefore           from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.44s T markorder            from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.46s T monad                from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.46s T mood                 from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.52s T morph                from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.54s T nodeID               from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.48s T nu                   from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.48s T number               from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.43s T person               from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.43s T punctuation          from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.64s T ref                  from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.64s T reference            from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.48s T roleclausedistance   from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.46s T sentence             from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.50s T sp                   from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.50s T sp_full              from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.54s T strongs              from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.44s T subj_ref             from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.43s T tense                from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.45s T type                 from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.44s T voice                from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.39s T wgclass              from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.33s T wglevel              from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.36s T wgnum                from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.35s T wgrole               from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.35s T wgrolelong           from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.39s T wgrule               from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.33s T wgtype               from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.50s T wordlevel            from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.50s T wordrole             from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6
   |     0.52s T wordrolelong         from ~/text-fabric-data/github/tonyjurg/Nestle1904LFT/tf/0.6

TF: TF API 12.1.5, tonyjurg/Nestle1904LFT/app v3, Search Reference
Data: tonyjurg - Nestle1904LFT 0.6, Character table, Feature docs

Node types

Name	# of nodes	# slots / node	% coverage
book	27	5102.93	100
chapter	260	529.92	100
verse	7943	17.35	100
sentence	8011	17.20	100
wg	105430	6.85	524
word	137779	1.00	100

Sets: no custom sets
Features:

Nestle 1904 (Low Fat Tree)

after

str

✅ Characters (eg. punctuations) following the word

book

str

✅ Book name (in English language)

booknumber

int

✅ NT book number (Matthew=1, Mark=2, ..., Revelation=27)

bookshort

str

✅ Book name (abbreviated)

case

str

✅ Gramatical case (Nominative, Genitive, Dative, Accusative, Vocative)

chapter

int

✅ Chapter number inside book

clausetype

str

✅ Clause type details (e.g. Verbless, Minor)

containedclause

str

🆗 Contained clause (WG number)

degree

str

✅ Degree (e.g. Comparitative, Superlative)

gloss

str

✅ English gloss

str

✅ Gramatical gender (Masculine, Feminine, Neuter)

headverse

str

✅ Start verse number of a sentence

junction

str

✅ Junction data related to a wordgroup

lemma

str

✅ Lexeme (lemma)

lex_dom

str

✅ Lexical domain according to Semantic Dictionary of Biblical Greek, SDBG (not present everywhere?)

str

✅ Lauw-Nida lexical classification (not present everywhere?)

markafter

str

🆗 Text critical marker after word

markbefore

str

🆗 Text critical marker before word

markorder

str

Order of punctuation and text critical marker

monad

int

✅ Monad (smallest token matching word order in the corpus)

mood

str

✅ Gramatical mood of the verb (passive, etc)

morph

str

✅ Morphological tag (Sandborg-Petersen morphology)

nodeID

str

✅ Node ID (as in the XML source data)

normalized

str

✅ Surface word with accents normalized and trailing punctuations removed

str

✅ Gramatical number (Singular, Plural)

number

str

✅ Gramatical number of the verb (e.g. singular, plural)

otype

str

person

str

✅ Gramatical person of the verb (first, second, third)

punctuation

str

✅ Punctuation after word

ref

str

✅ Value of the ref ID (taken from XML sourcedata)

reference

str

✅ Reference (to nodeID in XML source data, not yet post-processes)

roleclausedistance

str

⚠️ Distance to the wordgroup defining the syntactical role of this word

sentence

int

✅ Sentence number (counted per chapter)

str

✅ Part of Speech (abbreviated)

sp_full

str

✅ Part of Speech (long description)

strongs

str

✅ Strongs number

subj_ref

str

🆗 Subject reference (to nodeID in XML source data, not yet post-processes)

tense

str

✅ Gramatical tense of the verb (e.g. Present, Aorist)

type

str

✅ Gramatical type of noun or pronoun (e.g. Common, Personal)

unicode

str

✅ Word as it apears in the text in Unicode (incl. punctuations)

verse

int

✅ Verse number inside chapter

voice

str

✅ Gramatical voice of the verb (e.g. active,passive)

wgclass

str

✅ Class of the wordgroup (e.g. cl, np, vp)

wglevel

int

🆗 Number of the parent wordgroups for a wordgroup

wgnum

int

✅ Wordgroup number (counted per book)

wgrole

str

✅ Syntactical role of the wordgroup (abbreviated)

wgrolelong

str

✅ Syntactical role of the wordgroup (full)

wgrule

str

✅ Wordgroup rule information (e.g. Np-Appos, ClCl2, PrepNp)

wgtype

str

✅ Wordgroup type details (e.g. group, apposition)

word

str

✅ Word as it appears in the text (excl. punctuations)

wordlevel

str

🆗 Number of the parent wordgroups for a word

wordrole

str

✅ Syntactical role of the word (abbreviated)

wordrolelong

str

✅ Syntactical role of the word (full)

wordtranslit

str

🆗 Transliteration of the text (in latin letters, excl. punctuations)

wordunacc

str

✅ Word without accents (excl. punctuations)

oslots

none

Settings:

specified

apiVersion: 3
appName: tonyjurg/Nestle1904LFT
appPath:
C:/Users/tonyj/text-fabric-data/github/tonyjurg/Nestle1904LFT/app
commit: no value
css: ''
dataDisplay:
- excludedFeatures:
  - orig_order
  - verse
  - book
  - chapter
- noneValues:
  - none
  - unknown
  - no value
  - NA
  - ''
- showVerseInTuple: 0
- textFormat: text-orig-full
docs:
- docBase: https://github.com/tonyjurg/Nestle1904LFT/blob/main/docs/
- docPage: about
- docRoot: https://github.com/tonyjurg/Nestle1904LFT
- featureBase:
  https://github.com/tonyjurg/Nestle1904LFT/blob/main/docs/features/<feature>.md
interfaceDefaults: {fmt: layout-orig-full}
isCompatible: True
local: no value
localDir:
C:/Users/tonyj/text-fabric-data/github/tonyjurg/Nestle1904LFT/_temp
provenanceSpec:
- corpus: Nestle 1904 (Low Fat Tree)
- doi: 10.5281/zenodo.10182594
- org: tonyjurg
- relative: /tf
- repo: Nestle1904LFT
- repro: Nestle1904LFT
- version: 0.6
- webBase: https://learner.bible/text/show_text/nestle1904/
- webHint: Show this on the Bible Online Learner website
- webLang: en
- webUrl:
  https://learner.bible/text/show_text/nestle1904/<1>/<2>/<3>
- webUrlLex: {webBase}/word?version={version}&id=<lid>
release: no value
typeDisplay:
- book:
  - condense: True
  - hidden: True
  - label: {book}
  - style: ''
- chapter:
  - condense: True
  - hidden: True
  - label: {chapter}
  - style: ''
- sentence:
  - hidden: 0
  - label: #{sentence} (start: {book} {chapter}:{headverse})
  - style: ''
- verse:
  - condense: True
  - excludedFeatures: chapter verse
  - label: {book} {chapter}:{verse}
  - style: ''
- wg:
  - hidden: 0
  - label:
    #{wgnum}: {wgtype} {wgclass} {clausetype} {wgrole} {wgrule} {junction}
  - style: ''
- word:
  - base: True
  - features: lemma
  - featuresBare: gloss
  - surpress: chapter verse
writing: grc

TF API: names N F E L T S C TF Fs Fall Es Eall Cs Call directly usable

In [5]:

# The following will push the Text-Fabric stylesheet to this notebook (to facilitate proper display with notebook viewer)
N1904LFT.dh(N1904LFT.getCss())

4 - Add additional features ¶

back to TOC ¶

The following is optional.

4.1 - The official method ¶

back to TOC ¶

Still to be done: find good example

In [7]:

# load the app and data with additional features
N1904LFT = use ("tonyjurg/Nestle1904LFT:latest", mod=f"annotation/banks/sim/tf" hoist=globals())

  Input In [7]
    N1904LFT = use ("tonyjurg/Nestle1904LFT:latest", mod=f"annotation/banks/sim/tf" hoist=globals())
                                                                                    ^
SyntaxError: invalid syntax

4.2 - The unofficial method ¶

back to TOC ¶

Warning: to use this method it is critical to verify that ALL the following match:

most importantly, the Text-Fabric dataset should be based upon the same corpus (in the most literal sense of the word!)
the node range(s) (check output of command F.otype.all or values found in file otype.tf).
the slot order (i.e. the order of the wordsin the Text-Fabric corpus; usualy refered to as monad).

If these conditions are met, it is possible to copy the .tf files from the donor dataset to your local Text-Fabric directory..

4.3 - Additional dataset ¶

back to TOC ¶

Some additional dataset that should work with this Text-Fabric implementation are:

Dataset location	additions
CenterBLC	additional grammatical features, Bible Online Learner details

4.4 - Further reference ¶

back to TOC ¶

Further reference module tf.about.datasharing

5 - Using multiple Text-Fabric corpora ¶

back to TOC ¶

When using multiple Text-Fabric corpora there are a few things to take care of. The most important are to invocate function use twice using a different variables (name) to create two Advanced API's. In the following example two A (Advanced API) objects are created named CORPUS1 and CORPUS2:

CORPUS1 = use ( ... ) CORPUS2 = use ( ... )

IMPORTANT: When working with multiple corpora, do not add 'hoist=globals()' to the invocation!. See the comments on section hoist of function use.

In order to access to the variables F, L, T, and TF for the relevant CORPUS dataset, you need to first issue api = A.api like in the following example. This example will create two lists containing the nodes for that corpus where feature word has value λόγος. See also Hoisting.

# We also need to add the app reference before we can access the F API functions api=CORPUS1.api LogosList1=api.F.word.s(λόγος) api=CORPUS2.api LogosList2=api.F.word.s(λόγος)

Loading Text-Fabric (Nestle1904LFT)¶

Table of content ¶

1 - Introduction ¶

1.1 - Text-Fabric data versions ¶

2 - Preparation / installation¶

2.1 - Install Python ¶

2.2 - Install Text-Fabric ¶

2.3 - Raise rate limit on Github ¶

3 - Load Text-Fabric into memory ¶

3.1 - Load the code ¶

3.2 - Load app and data ¶

4 - Add additional features¶

4.1 - The official method¶

4.2 - The unofficial method¶

4.3 - Additional dataset¶

4.4 - Further reference¶

5 - Using multiple Text-Fabric corpora¶

2 - Preparation / installation ¶

4 - Add additional features ¶

4.1 - The official method ¶

4.2 - The unofficial method ¶

4.3 - Additional dataset ¶

4.4 - Further reference ¶

5 - Using multiple Text-Fabric corpora ¶