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Embedding epistemic modals in English: A corpus-based study

Paper · 2012 · Valentine Hacquard and Alexis Wellwood

Summary

The authors ask whether epistemic modals add to a sentence's truth conditions or only signal the speaker's attitude. That debate depends on whether such modals can sit under other operators. To test this, they ran a large corpus study on the New York Times portion of the English Gigaword Corpus, which they parsed automatically with the Huang & Harper (2009) parser. They counted modals in three embedding environments: if-clause antecedents, questions, and complements of attitude predicates. They used might as an epistemic proxy and can as a root proxy. For must, which allows both readings, they hand-classified samples, and they also looked at finite and infinitival have to. Epistemic readings do occur embedded, which favours a truth-conditional analysis. However, they are much rarer than root readings in conditionals and matrix questions. Under attitudes they appear with belief and communication verbs but largely avoid desire and command predicates. The authors conclude that epistemics carry semantic content but may need special licensing conditions.

Key points

  • The parsed dataset has 15,691,859 sentences: 149,219 contain might, 88,859 must, and 475,590 can.
  • Might appears in conditional antecedents in only 0.02% of its tokens, against 1.95% for can. In matrix questions the figures are 0.35% vs 3.78%. Under attitude predicates the pattern reverses: 11.56% vs 7.75%. All three differences are significant (p < 0.001, Fisher's exact test).
  • A sample of 400 matrix declaratives showed must is epistemic about 17% of the time; this served as the baseline. Epistemic must is significantly underrepresented in conditionals and questions, but its rate under attitudes does not differ from the baseline.
  • Parser errors were filtered by checking whether the governing predicate can select a clausal or question complement. For embedded questions, 45.2% of hits were dropped, mostly free relatives the parser mistook for questions.
  • An appendix sorts attitude verbs and adjectives into classes: acceptance, possibility/certainty, emotive, desideratives/directives, futures/perception/fiction, and other. Predicates that embedded might at least five times are marked.

Interesting ideas

  • I1. Using lexical items with a fixed reading (might = epistemic, can = root) as proxies lets you measure a semantic category over huge parsed data without hand-labelling every token.
  • I2. Each item's rate in an environment is compared against its own rate in the rest of the corpus, not compared raw, so frequency differences between words do not mislead.
  • I3. The selectional properties of the head predicate serve as a sanity filter on parser output, catching relative clauses and free relatives misparsed as complements.
  • I4. Attitude predicates are grouped by meaning class (belief/report vs desire/command), and these classes predict whether an epistemic can appear in the complement.
  • I5. A modal's position relative to operators (if-clause, question, attitude) shifts its reading, so the scope of uncertainty depends on structure, not only on the word itself.

For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

  • I1 (learn): Pick unambiguous anchor words to estimate frame-type distributions on silver data cheaply, then hand-check only the ambiguous words like must.
  • I2 (learn): Evaluation of whether a parser over- or under-attaches a construction should use this per-item baseline as a built-in control.
  • I3 (tree): Add a repair/check rule that flags ccomp arcs under heads that cannot take clausal complements, a likely relcl or free-relative error.
  • I4 (world): Store this attitude-class feature in the verb lexicon so embedded might under think becomes the holder's uncertain belief, while desire verbs get no epistemic reading.
  • I5 (frames): When building frames, attach epistemic modals to the attitude holder's belief state rather than the speaker's when they sit inside a complement clause.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of Maryland, College ParkCollege Park · United States83 works · 23,784 citations

📚 Shelves 5 Computer Science · 9,086 works Artificial Intelligence · 8,889 works Arts and Humanities · 9,296 works Language and Linguistics · 9,206 works Philosophy · 211 works

🧭 Topics 1 English · 1,373 works

Cite

Cite as Valentine Hacquard and Alexis Wellwood. 2012. Embedding epistemic modals in English: A corpus-based study. Semantics and Pragmatics.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.3765/sp.5.4

@article{hacquard2012embedding,
  title = {{Embedding epistemic modals in English: A corpus-based study}},
  author = {Valentine Hacquard and Alexis Wellwood},
  journal = {Semantics and Pragmatics},
  year = {2012},
  doi = {10.3765/sp.5.4},
  url = {https://doi.org/10.3765/sp.5.4}
}

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