Genre Comparison — Morphological Patterns Across Biblical Literature¶

Different literary genres use Hebrew and Greek grammar in systematically different ways:

• OT Narrative prose is dominated by the wayyiqtol (Consecutive Imperfect) — the narrative past tense that drives sequential action
• OT Poetry and Prophecy favor the yiqtol (Imperfect) and qatal (Perfect), reflecting ongoing states and vivid-present discourse
• OT Legal texts have higher construct-chain density and noun-heavy POS profiles
• NT Epistolary letters use Present and Perfect more than narratives
• NT Pauline letters have higher Passive voice ratios — "theological passives" avoid naming God as subject
• NT Revelation has dense Participle usage and unique vocabulary

This notebook quantifies those patterns using the TAHOT (OT) and TAGNT (NT) morphological databases.

In [ ]:

import sys
sys.path.insert(0, '../../../src')

import pandas as pd
from IPython.display import Image
from bible_grammar.genre_compare import (
    genre_compare,
    print_genre_compare,
    genre_heatmap,
    genre_report,
    OT_GENRES,
    NT_GENRES,
)

import sys sys.path.insert(0, '../../../src') import pandas as pd from IPython.display import Image from bible_grammar.genre_compare import ( genre_compare, print_genre_compare, genre_heatmap, genre_report, OT_GENRES, NT_GENRES, )

---

1. OT Verb Stem Distribution by Genre¶

Hebrew verb stems (binyanim) encode voice, valency, and action intensity:

• Qal — simple active (~68% of all OT verbs)
• Niphal — passive/reflexive
• Piel — intensive/factitive/declarative
• Hiphil — causative-active
• Hophal — causative-passive
• Pual — passive of Piel
• Hithpael — reflexive-intensive

Across genres, the Qal dominates everywhere, but the proportions of derived stems differ — wisdom poetry uses more Piel (emphatic speech acts); legal texts use more Hiphil (causative commands).

In [ ]:

print_genre_compare('OT', feature='verb_stem')

print_genre_compare('OT', feature='verb_stem')

In [ ]:

path = genre_heatmap('OT', feature='verb_stem')
print(f'Saved: {path}')
Image(str(path))

path = genre_heatmap('OT', feature='verb_stem') print(f'Saved: {path}') Image(str(path))

---

2. OT Verb Conjugation by Genre¶

The conjugation profile is the clearest genre marker in Biblical Hebrew:

• Consecutive Imperfect (wayyiqtol) dominates Torah and Historical narrative — it is the engine of sequential past-tense storytelling
• Imperfect (yiqtol) and Participle are proportionally higher in Wisdom and Prophets — reflecting habitual, ongoing, or vivid-present usage
• Perfect (qatal) is relatively stable across genres but higher in prophetic and wisdom speech
• Imperative is highest in legal texts (Leviticus, Numbers) and prophetic commands

The difference between Historical narrative and Wisdom poetry is the most visually striking contrast in the heatmap.

In [ ]:

print_genre_compare('OT', feature='verb_conjugation')

print_genre_compare('OT', feature='verb_conjugation')

In [ ]:

path = genre_heatmap('OT', feature='verb_conjugation')
print(f'Saved: {path}')
Image(str(path))

path = genre_heatmap('OT', feature='verb_conjugation') print(f'Saved: {path}') Image(str(path))

---

3. OT Part-of-Speech Mix by Genre¶

The ratio of verbs to nouns shifts by genre: narrative is verb-heavy (action sequences), while poetry and law are noun-heavy (description, categorization). Prepositions are proportionally higher in construct-chain-rich legal and wisdom texts.

In [ ]:

print_genre_compare('OT', feature='pos')

print_genre_compare('OT', feature='pos')

In [ ]:

# Raw DataFrame for custom analysis
ot_pos_df = genre_compare('OT', feature='pos', normalize=True)
ot_pos_df

# Raw DataFrame for custom analysis ot_pos_df = genre_compare('OT', feature='pos', normalize=True) ot_pos_df

---

4. NT Verb Tense by Genre¶

Greek verb tenses encode both time and aspect:

• Aorist (punctiliar past) dominates narrative sections (Gospels, Acts) — the default past-tense tense
• Present (imperfective) dominates epistolary and didactic writing — habitual, ongoing, gnomic
• Perfect (R-form) marks completed action with ongoing relevance — highest in Hebrews and John's Gospel
• Imperfect (ongoing past) appears in narrative sections for background activity

The contrast between Gospels/Acts (Aorist-heavy) and Pauline letters (Present-heavy) reflects narrative vs. instructional register.

In [ ]:

print_genre_compare('NT', feature='verb_tense')

print_genre_compare('NT', feature='verb_tense')

In [ ]:

path = genre_heatmap('NT', feature='verb_tense')
print(f'Saved: {path}')
Image(str(path))

path = genre_heatmap('NT', feature='verb_tense') print(f'Saved: {path}') Image(str(path))

---

5. NT Verb Voice by Genre¶

Voice distribution reveals discourse strategy:

• Active dominates everywhere but is proportionally highest in Gospels/Acts narrative
• Passive is elevated in Pauline letters — the "divine passive" (theological passive) avoids naming God as direct agent (e.g., "you were called," "grace was given")
• Middle/Deponent reflects grammaticalized middle constructions common in Greek idiom

Higher Passive ratios in Pauline and General letters is a recognized stylistic feature.

In [ ]:

print_genre_compare('NT', feature='verb_voice')

print_genre_compare('NT', feature='verb_voice')

In [ ]:

path = genre_heatmap('NT', feature='verb_voice')
print(f'Saved: {path}')
Image(str(path))

path = genre_heatmap('NT', feature='verb_voice') print(f'Saved: {path}') Image(str(path))

---

6. NT Verb Mood by Genre¶

Mood distribution marks modality and clause type:

• Indicative dominates across all genres (main-clause statements)
• Participle is proportionally highest in Revelation and General letters — dense attributive and predicative participial clauses
• Subjunctive is highest in Pauline letters — purpose clauses (ἵνα + subjunctive), conditional sentences, and hortatory usage
• Imperative is relatively stable but slightly elevated in epistolary paraenesis (ethical commands)

In [ ]:

print_genre_compare('NT', feature='verb_mood')

print_genre_compare('NT', feature='verb_mood')

In [ ]:

# Raw DataFrame
nt_mood_df = genre_compare('NT', feature='verb_mood', normalize=True)
nt_mood_df

# Raw DataFrame nt_mood_df = genre_compare('NT', feature='verb_mood', normalize=True) nt_mood_df

---

7. Full Report¶

Generate a comprehensive Markdown genre comparison report with all heatmaps for OT and NT:

In [ ]:

report_path = genre_report()
print(f"Report saved: {report_path}")

report_path = genre_report() print(f"Report saved: {report_path}")

---

8. Quick Reference¶

from bible_grammar.genre_compare import (
    genre_compare,
    print_genre_compare,
    genre_heatmap,
    genre_report,
    OT_GENRES,
    NT_GENRES,
)

# Genre / section registries
OT_GENRES   # {'Torah': [...], 'Historical': [...], 'Wisdom': [...], 'Prophets': [...]}
NT_GENRES   # {'Gospels & Acts': [...], 'Pauline': [...], 'General & Rev': [...]}

# Available features:
#   OT: 'verb_stem', 'verb_conjugation', 'pos', 'noun_state'
#   NT: 'verb_tense', 'verb_voice', 'verb_mood', 'pos'

# Raw DataFrame (normalize=True gives row percentages; False gives counts)
genre_compare('OT', feature='verb_stem', normalize=True)
genre_compare('NT', feature='verb_tense', normalize=False)

# Formatted terminal table
print_genre_compare('OT', feature='verb_stem')
print_genre_compare('NT', feature='verb_tense')
print_genre_compare('OT', feature='verb_conjugation')
print_genre_compare('NT', feature='verb_voice')
print_genre_compare('NT', feature='verb_mood')

# Heatmap chart — returns path to saved PNG
genre_heatmap('OT', feature='verb_stem')
genre_heatmap('OT', feature='verb_conjugation')
genre_heatmap('NT', feature='verb_tense')
genre_heatmap('NT', feature='verb_voice')
genre_heatmap('OT', output_path='output/charts/ot-genre-stems.png')

# Full Markdown report with all heatmaps
genre_report(output_dir='output/reports/both/genre')
genre_report(ot_features=['verb_stem', 'pos'], nt_features=['verb_tense'])