CONT Verbal contractions

Biber N59 Xiao N99 MFTE CONT Bohmann 165

Definition

Contracted verb forms: n’t, ’ll, ’re, ’ve, ’s (verbal), ’d.

Detection Rules

mfte

MFTE counts: ‘s/’re/’ve/’m only when POS-tagged as verbs; n’t always; ‘ll/’d always.

p1 
cql[word="'s|'re|'ve|'m" & pos="VBZ|VBP|VB|VBD|VBN|VBG|MD"]
p2 
cql[word="n't"]
p3 
cql[word="'ll|'d"]
combine: p1 | p2 | p3

Requires: word, pos

Raw text regex for contractions. No NLP pipeline needed.

regex\b\w+'(t|ll|re|ve|s|d)\b

Requires: word

pybiber

pybiber blob patterns: ’\S*_v\S* (verb-tagged contractions), ’\S*_md (modal contractions), n’t_\S* (any-tagged negation). The verb POS constraint prevents counting possessive ‘s that leaks through spaCy’s POS tagger as non-POS tags. p5 catches unsplit contractions like “birds’ll” tagged as VBP.

p1 
cql[word="'s|'re|'ve|'m" & pos="VB.*"]
p2 
cql[word="'ll" & pos="MD"]
p3 
cql[word="'d" & pos="MD|VB.*"]
p4 
cql[word="n't"]
p5 
cql[word=".*'ll" & pos="VB.*"]
combine: p1 | p2 | p3 | p4 | p5

Requires: word, pos

Normalization

Per finite_verbs

Examples

I don’t know.

Source: le_foll_2024

It isn’t my problem.

Source: le_foll_2024

You’ll have to deal with it.

Source: le_foll_2024

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
  • grieve_2023 — Grieve, Jack (2023) : Register variation explains stylometric authorship analysis
  • bohmann_2019 — Bohmann, Axel (2019) : Variation in English Worldwide: Varieties and Genres in a Quantitative Perspective

Notes

Third-highest loading on D1.

View YAML source