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Record W2508414753 · doi:10.1515/ling-2016-0019

The lexicon in Functional Discourse Grammar: Theory, typology, description

2016· article· en· W2508414753 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLinguistics · 2016
Typearticle
Languageen
FieldComputer Science
TopicNatural Language Processing Techniques
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsLexemeLexiconLinguisticsComputer scienceMorphemeGrammarNatural language processingArtificial intelligenceLexical itemFrame (networking)Philosophy

Abstract

fetched live from OpenAlex

Abstract This paper discusses the treatment of the lexicon in Functional Discourse Grammar (FDG) and serves to provide a general introduction to the theoretical framework and its formalizations, in particular for readers who may not be intimately familiar with it. After outlining the general architecture of the model, we discuss the position, content and function of the FDG lexicon in more detail. The FDG lexicon is often called the Fund, as it contains more than just a collection of lexemes. The Fund is conceived of as a storehouse containing all unpredictable linguistic knowledge in the form of various types of primitives. In addition to a lexicon proper this includes structural and grammatical primitives that feed the grammar, such as: pragmatic and semantic frames, functions and operators; morphosyntactic and phonological templates and operators; and suppletive forms. The “lexicon proper” contains grammatical morphemes and suppletive forms in addition to lexemes; the collection of frames and templates is sometimes called the “structicon”; and operators and functions constitute what may be called the “grammaticon”. The division of labor between the Fund and the Grammar is illustrated by showing how FDG treats lexeme, word and frame formation: lexeme formation is located in the Fund, word formation is located in the Grammar, and frame formation may be located in either, depending on the particular frame or the approach of the analyst. We then discuss the form and content of lexical entries. This has been a topic of some discussion recently, and several of the contributions to this special issue contain proposals in this area. The central question here is how best to capture the existence of common or even default associations between primitives at different levels of representation while still allowing for the occurrence of mismatches. Mismatches allow us to account for phenomena like coercion and other creative uses of the linguistic apparatus available to the language user. Next we address the construction of lexical meaning, showing where FDG draws the line between semantics on the one hand and pragmatics, contextual factors, and conceptualization on the other hand. Here again, different points of view coexist and several contributions contain proposals for how to represent lexical meaning. Our final section briefly introduces the other contributions to this special issue.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.914
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.281
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it