NN Total other nouns
Definition
Residual noun count: all nouns (including proper nouns) minus nominalizations and gerunds. A marker of informational density.
Detection Rules
Uses cat refinement for NOMZ (refines: NN|NNS). GER is explicit exclusion because it matches VBG tokens (not NN) — conceptual subtraction, not index overlap.
cql[cat="NN|NNS|NNP|NNPS"]
combine: _ & !GER
pybiber
All nouns (NOUN/PROPN coarse POS, no hyphens). pybiber uses coarse POS which excludes pronouns tagged NN (nothing, something, anyone, anything). Only NOUN-tagged gerunds are subtracted (not PROPN like “Building”).
cql[upos="NOUN|PROPN" & word!=".*-.*"]
ger_noun
cql[word=".*ings?$" & upos="NOUN" & dep="nsubj|dobj|pobj|nsubjpass" & word!={words_ger_stop}]
combine: _ & !NOMZ & !ger_noun
Words: ger_stop (55 items)
according
anything
beijing
bing
bings
boeing
bring
ceiling
ceilings
cling
clings
darling
ding
dings
during
evening
evenings
everything
fling
flings
inning
innings
irving
king
kings
morning
mornings
nothing
notwithstanding
offspring
offsprings
outstanding
ping
pings
ring
rings
sing
sings
something
spring
springs
sterling
sting
stings
string
strings
thanksgiving
thanksgivings
thing
things
wedding
wing
wings
wrongdoing
wyoming
Normalization
Per words
Sources
- biber_1988 — Biber, Douglas (1988) : Variation across Speech and Writing
- mfte — Le Foll, Elen & Shakir, Muhammad (2023/2025) : Multi-Feature Tagger of English (MFTE) — Python version
- pybiber — Brown, David West & Reinhart, Alex (2026) : pybiber — Python package for linguistic feature extraction and Multi-Dimensional Analysis
- xiao_2009 — Xiao, Richard (2009) : Multidimensional analysis and the study of world Englishes
Notes
Strongest negative loading on D1. Biber’s f_16 “other nouns” is the residual after subtracting nominalizations (f_14) and gerunds (f_15). pybiber also excludes hyphenated tokens.