Niphal (נִפְעַל) Verb Morphology — Biblical Hebrew¶

Statistical analysis of the Niphal stem across the Hebrew Old Testament. For use in a 2nd-year Biblical Hebrew syntax course.

The Niphal is the primary reflexive-passive stem of Biblical Hebrew, formed with a נ (nun) prefix in the perfect (נִשְׁמַר) and a doubled middle consonant in the imperfect (יִשָּׁמֵר). It is the most common derived stem after the Qal and expresses passive, reflexive, reciprocal, middle/stative, and tolerative meanings.

Sections:

1. Overview & Key Statistics
2. Conjugation (Tense/Aspect) Distribution
3. Most Frequent Niphal Roots
4. Root × Conjugation Cross-Table
5. Distribution Across Books
6. Niphal vs. Other Stems by Genre
7. Niphal-Dominant Roots
8. Semantic Function Categories
9. Generate Full Report

In [ ]:

import sys
sys.path.insert(0, '../../../src')
from bible_grammar import (
    print_niphal_overview, print_niphal_conjugation,
    print_niphal_top_roots, print_niphal_root_conjugation,
    print_niphal_book_distribution, print_niphal_dominant_roots,
    print_niphal_semantic_categories,
    niphal_conjugation_chart, niphal_book_chart,
    niphal_stem_chart, niphal_root_heatmap,
    niphal_semantic_chart, niphal_top_roots_chart,
    niphal_report,
    niphal_data, niphal_conjugation_profile, niphal_top_roots,
    niphal_book_distribution, niphal_dominant_roots,
    niphal_stem_comparison, niphal_semantic_categories,
)
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
print('Ready.')

import sys sys.path.insert(0, '../../../src') from bible_grammar import ( print_niphal_overview, print_niphal_conjugation, print_niphal_top_roots, print_niphal_root_conjugation, print_niphal_book_distribution, print_niphal_dominant_roots, print_niphal_semantic_categories, niphal_conjugation_chart, niphal_book_chart, niphal_stem_chart, niphal_root_heatmap, niphal_semantic_chart, niphal_top_roots_chart, niphal_report, niphal_data, niphal_conjugation_profile, niphal_top_roots, niphal_book_distribution, niphal_dominant_roots, niphal_stem_comparison, niphal_semantic_categories, ) import pandas as pd import matplotlib.pyplot as plt import matplotlib.image as mpimg print('Ready.')

---

1. Overview & Key Statistics¶

The Niphal is the reflexive-passive stem of Biblical Hebrew. It prefixes נִ- in the perfect; in the imperfect the nun assimilates, producing a doubled middle consonant (e.g. יִשָּׁמֵר).

Five main semantic functions:

• Passive: נִשְׁמַר 'was kept' (← Qal שָׁמַר 'kept')
• Reflexive: נִסְתַּר 'hid himself'
• Reciprocal: נוֹעֲדוּ 'met each other'
• Middle/Stative: נִכְלַם 'felt ashamed'
• Tolerative: נִמְכַּר 'allowed himself to be sold'

Notable Niphal roots: נִבְרָא (be created), נִמְצָא (be found), נִשְׁמַר (be kept/guarded).

In [ ]:

print_niphal_overview()

print_niphal_overview()

---

2. Conjugation (Tense/Aspect) Distribution¶

Which conjugation types does the Niphal appear in most frequently? This tells us where in discourse the Niphal is used — passive narrative chains, reflexive commands, divine passive declarations, etc.

In [ ]:

print_niphal_conjugation()  # Whole OT

# Compare Genesis (narrative) vs. Psalms (poetry)
print_niphal_conjugation('Gen')
print_niphal_conjugation('Psa')

print_niphal_conjugation() # Whole OT # Compare Genesis (narrative) vs. Psalms (poetry) print_niphal_conjugation('Gen') print_niphal_conjugation('Psa')

In [ ]:

from IPython.display import Image
path = niphal_conjugation_chart()
print(f'Saved: {path}')
Image(str(path))

from IPython.display import Image path = niphal_conjugation_chart() print(f'Saved: {path}') Image(str(path))

---

3. Most Frequent Niphal Roots¶

These are the verbs students will encounter most often in the Niphal.

• נָתַן (natan) — appears as 'was given'
• מָצָא (matsa) — 'was found'
• בָּרָא (bara) — exclusively Niphal for passive creation
• שָׁמַר (shamar) — 'was kept, guarded'

In [ ]:

print_niphal_top_roots(25)

print_niphal_top_roots(25)

In [ ]:

from IPython.display import Image
path = niphal_top_roots_chart(20)
print(f'Saved: {path}')
Image(str(path))

from IPython.display import Image path = niphal_top_roots_chart(20) print(f'Saved: {path}') Image(str(path))

---

4. Root × Conjugation Cross-Table¶

Which conjugations does each root favor? This reveals important usage patterns:

• נָתַן (give): qatal-heavy in the Niphal → 'was given' in legal/narrative context
• יָלַד (bear): participle-heavy → ongoing birth records in genealogies
• שָׁבַע (swear): perfect-heavy → 'swore to himself' (reflexive oath formulas)
• קָרָא (call): imperfect-heavy → 'shall be called' (future naming)

In [ ]:

print_niphal_root_conjugation(top_n=15)

print_niphal_root_conjugation(top_n=15)

In [ ]:

from IPython.display import Image
path = niphal_root_heatmap(top_n=15)
print(f'Saved: {path}')
Image(str(path))

from IPython.display import Image path = niphal_root_heatmap(top_n=15) print(f'Saved: {path}') Image(str(path))

---

5. Distribution Across Books¶

Jeremiah leads in raw Niphal count — its dense prophetic passive speech (divine decrees, judgments declared) drives high Niphal frequency. Leviticus shows a high Niphal percentage relative to book size due to the frequent passive constructions in purity laws.

In [ ]:

print_niphal_book_distribution(top_n=20)

print_niphal_book_distribution(top_n=20)

In [ ]:

from IPython.display import Image
path = niphal_book_chart()
print(f'Saved: {path}')
Image(str(path))

from IPython.display import Image path = niphal_book_chart() print(f'Saved: {path}') Image(str(path))

---

6. Niphal vs. Other Stems by Genre¶

The Niphal (shown in orange) typically represents 5–10% of verbs per book. Compare with Qal (60–80%), Hiphil (9–16%), Piel (7–15%). Leviticus has a notably high Niphal percentage due to legal purity language.

In [ ]:

from bible_grammar import niphal_stem_comparison
df = niphal_stem_comparison(['Gen', 'Exo', 'Lev', 'Deu', 'Psa', 'Isa', 'Jer', 'Pro'])
print(df.to_string())

from bible_grammar import niphal_stem_comparison df = niphal_stem_comparison(['Gen', 'Exo', 'Lev', 'Deu', 'Psa', 'Isa', 'Jer', 'Pro']) print(df.to_string())

In [ ]:

from IPython.display import Image
path = niphal_stem_chart(['Gen', 'Exo', 'Lev', 'Deu', 'Psa', 'Isa', 'Jer', 'Pro'])
print(f'Saved: {path}')
Image(str(path))

from IPython.display import Image path = niphal_stem_chart(['Gen', 'Exo', 'Lev', 'Deu', 'Psa', 'Isa', 'Jer', 'Pro']) print(f'Saved: {path}') Image(str(path))

---

7. Niphal-Dominant Roots (>=70%)¶

These roots are functionally Niphal-only — they appear almost exclusively in the Niphal, with no separate Qal form in significant use. Students should recognize these as verbs whose basic meaning already expresses a passive or reflexive state.

Highlights:

• נִלְחַם 'fought' — the Qal scarcely exists; all warfare fighting is Niphal
• נִשְׁבַּע 'swore' — the reflexive oath formula is standard (swore to himself)
• נִבְרָא 'was created' — בָּרָא takes God as subject in Qal; the Niphal is passive

In [ ]:

print_niphal_dominant_roots(top_n=25)

print_niphal_dominant_roots(top_n=25)

In [ ]:

# Get raw data for custom analysis
dom = niphal_dominant_roots(min_pct=90, min_tokens=10)
print('Roots >=90% Niphal with >=10 tokens:')
print(dom[['root', 'lemma', 'niphal_count', 'hif_pct', 'top_gloss']].to_string(index=False))

# Get raw data for custom analysis dom = niphal_dominant_roots(min_pct=90, min_tokens=10) print('Roots >=90% Niphal with >=10 tokens:') print(dom[['root', 'lemma', 'niphal_count', 'hif_pct', 'top_gloss']].to_string(index=False))

---

8. Semantic Function Categories¶

Categories derived from MACULA English gloss annotations. The Niphal spans passive, reflexive, reciprocal, middle/stative, and tolerative functions — making it the most semantically versatile derived stem.

In [ ]:

print_niphal_semantic_categories()

print_niphal_semantic_categories()

In [ ]:

from IPython.display import Image
path = niphal_semantic_chart()
print(f'Saved: {path}')
Image(str(path))

from IPython.display import Image path = niphal_semantic_chart() print(f'Saved: {path}') Image(str(path))

---

9. Generate Full Report¶

Generates a Markdown report with all tables and embeds all 6 charts. Saved to output/reports/ot/verbs/niphal_report.md.

In [ ]:

path = niphal_report()
print(f'Report: {path}')

path = niphal_report() print(f'Report: {path}')

---

Quick Reference¶

# All functions available via:
from bible_grammar import (
    # Data
    niphal_data,                  # all tokens (or filtered by book)
    niphal_conjugation_profile,   # type_ distribution DataFrame
    niphal_top_roots,             # most frequent roots
    niphal_root_conjugation,      # root x conjugation crosstab
    niphal_book_distribution,     # count + % per book
    niphal_stem_comparison,       # all stems % by book
    niphal_dominant_roots,        # roots >=X% Niphal
    niphal_semantic_categories,   # semantic function counts
    # Print
    print_niphal_overview,
    print_niphal_conjugation,
    print_niphal_top_roots,
    print_niphal_root_conjugation,
    print_niphal_book_distribution,
    print_niphal_dominant_roots,
    print_niphal_semantic_categories,
    # Charts
    niphal_conjugation_chart,     # horizontal bar
    niphal_book_chart,            # bar + line dual-axis
    niphal_stem_chart,            # stacked bar (Niphal in orange)
    niphal_root_heatmap,          # root x conjugation heatmap
    niphal_semantic_chart,        # pie chart
    niphal_top_roots_chart,       # horizontal bar
    # Report
    niphal_report,                # full Markdown + all charts
)

Slash commands:

• /niphal overview — key statistics
• /niphal conj [book] — conjugation profile
• /niphal roots [n] — top roots
• /niphal roottable — root x conjugation table
• /niphal books — distribution across books
• /niphal dominant — Niphal-only roots
• /niphal semantic — semantic function breakdown
• /niphal report — full report + charts