{ "cells": [ { "cell_type": "markdown", "id": "f2637008-fceb-47b8-86ac-42633829b391", "metadata": {}, "source": [ "# Constituents order and phrase structure (Nestle1904GBI)\n", "\n", "**Work in progress**" ] }, { "cell_type": "markdown", "id": "c7a43f6f-08b8-40da-a1f5-f9cb323c964f", "metadata": {}, "source": [ "## Table of content \n", "* 1 - Introduction\n", " * 1.1 - Why is this relevant?\n", " * 1.2 - Translating into Text-Fabric queries\n", "* 2 - Load Text-Fabric app and data\n", "* 3 - Performing the queries\n", " * 3.1 - TBD\n", " * 3.2 - TBD\n", "* 4 - Footnotes and attribution\n", "* 5 - Required libraries" ] }, { "cell_type": "markdown", "id": "99c8eed2-94dd-4b62-ba6a-487386e93422", "metadata": {}, "source": [ "# 1 - Introduction \n", "##### [Back to TOC](#TOC)\n", "\n", "Place holder for further investigation" ] }, { "cell_type": "markdown", "id": "f1c6fbd9-2cca-41aa-b6f1-0ef852857dff", "metadata": {}, "source": [ "## 1.1 - Why is this relevant? \n", "\n", "The constituent order may have exegetical relevance." ] }, { "cell_type": "markdown", "id": "1ad657ef-0133-413e-87bb-9ef12e67573f", "metadata": {}, "source": [ "## 1.2 - Translating into Text-Fabric queries \n", "\n", "The rough idea is to first determine the sets of clauses by constituent order.\n", "Secondly determine relative order of adjectives in phrases.\n", "Lastly perform statistic analysis on the percentate of certain phrase structures for the various constituent order types." ] }, { "cell_type": "markdown", "id": "b671c880-a546-4849-9384-487ed4a4531a", "metadata": {}, "source": [ "# 2 - Load Text-Fabric app and data \n", "##### [Back to TOC](#TOC)" ] }, { "cell_type": "code", "execution_count": 1, "id": "e72dbefe-43c5-4a03-a8f6-7b885f4e57ea", "metadata": { "tags": [] }, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 1, "id": "0825dd50-e607-485f-85f0-83e85ad289f0", "metadata": {}, "outputs": [], "source": [ "# Loading the Text-Fabric code\n", "# Note: it is assumed Text-Fabric is installed in your environment\n", "from tf.fabric import Fabric\n", "from tf.app import use" ] }, { "cell_type": "code", "execution_count": 2, "id": "72661b2a-d195-44cb-a524-1d542784b8d0", "metadata": { "scrolled": true, "tags": [] }, "outputs": [ { "data": { "text/markdown": [ "**Locating corpus resources ...**" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "app: ~/text-fabric-data/github/tonyjurg/Nestle1904GBI/app" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "data: ~/text-fabric-data/github/tonyjurg/Nestle1904GBI/tf/0.4" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", " Text-Fabric: Text-Fabric API 11.4.10, tonyjurg/Nestle1904GBI/app v3, Search Reference
\n", " Data: tonyjurg - Nestle1904GBI 0.4, Character table, Feature docs
\n", "
Node types\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "\n", "\n", " \n", " \n", " \n", " \n", "\n", "
Name# of nodes# slots/node% coverage
book275102.93100
chapter260529.92100
sentence572024.09100
verse794317.35100
clause161248.54100
phrase726741.90100
word1377791.00100
\n", " Sets: no custom sets
\n", " Features:
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Nestle 1904 (GBI nodes)\n", "
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str
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str
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int
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str
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str
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int
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int
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str
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str
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\n", "\n", "
\n", "
\n", "formaltag\n", "
\n", "
str
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\n", "\n", "
\n", "
\n", "functionaltag\n", "
\n", "
str
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\n", "
\n", "gloss\n", "
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str
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\n", "
\n", "gn\n", "
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str
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\n", "
\n", "lemma\n", "
\n", "
str
\n", "\n", " \n", "\n", "
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\n", "
\n", "lex_dom\n", "
\n", "
str
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\n", "ln\n", "
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str
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\n", "monad\n", "
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int
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str
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str
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\n", "nu\n", "
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str
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\n", "
\n", "number\n", "
\n", "
str
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\n", "
\n", "otype\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "person\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "phrase\n", "
\n", "
int
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\n", "\n", "
\n", "
\n", "phrasefunction\n", "
\n", "
str
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\n", "phrasefunctionlong\n", "
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str
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\n", "phrasetype\n", "
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str
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\n", "sentence\n", "
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int
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str
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\n", "\n", "
\n", "
\n", "splong\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "strongs\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "subj_ref\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "tense\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "type\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "verse\n", "
\n", "
int
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "voice\n", "
\n", "
str
\n", "\n", " \n", "\n", "
\n", "\n", "
\n", "
\n", "word\n", "
\n", "
str
\n", "\n", " \n", "\n", "
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\n", "oslots\n", "
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none
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Text-Fabric API: names N F E L T S C TF directly usable

" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# load the N1904 app and data\n", "N1904 = use (\"tonyjurg/Nestle1904GBI\", version=\"0.4\", hoist=globals())" ] }, { "cell_type": "code", "execution_count": 3, "id": "4a2ed92b-9517-4b32-929e-cb02f9815f61", "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# The following will push the Text-Fabric stylesheet to this notebook (to facilitate proper display with notebook viewer)\n", "N1904.dh(N1904.getCss())" ] }, { "cell_type": "markdown", "id": "217ec003-7e50-4fa6-982b-67b1dc880b52", "metadata": {}, "source": [ "# 3 - Performing the queries \n", "##### [Back to TOC](#TOC)" ] }, { "cell_type": "markdown", "id": "1b3dd917-8fb5-400b-91a6-6b09e2630bba", "metadata": { "tags": [] }, "source": [ "## 3.1 - Determine the conditions \n", "\n", "This code will produce ....." ] }, { "cell_type": "markdown", "id": "b81aa6ac-deed-444b-97b6-2bab15d42025", "metadata": {}, "source": [ "# 4 - Attribution and footnotes\n", "##### [Back to TOC](#TOC)\n", "\n", "### Attribution:\n", "\n", "Thanks to Prof. Willem van Peursen (VU) for pointing me to the following:\n", ">In Peter James Silzer and Thomas John Finley, How Biblical Languages Work, there is a chapter on Putting Words together: phrases and clauses, which contains some observations on constitutent order (SVO, VSO etc.) and internal phrase structure (e.g. relative order of adjectives)." ] }, { "cell_type": "markdown", "id": "eba9484d-24fb-4c0b-9c41-152ca6f43a1b", "metadata": {}, "source": [ "# 5 - Required libraries \n", "##### [Back to TOC](#TOC)" ] }, { "cell_type": "markdown", "id": "e103b001-083c-4df2-94db-67014525a450", "metadata": {}, "source": [ "The scripts in this notebook require (beside `text-fabric`) the following Python libraries to be installed in the environment:\n", "\n", " {none}\n", "\n", "You can install any missing library from within Jupyter Notebook using either`pip` or `pip3`." ] }, { "cell_type": "code", "execution_count": null, "id": "88210517-f05b-404d-a9e1-b54376176a0c", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.5" } }, "nbformat": 4, "nbformat_minor": 5 }