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Record W40576911 · doi:10.25596/jalc-2004-333

Context Derivation Sets and Context-Free Normal Forms

2004· article· en· W40576911 on OpenAlexaff
Charlotte L. Miller

Bibliographic record

VenueJustus-Liebig-Universität Gießen · 2004
Typearticle
Languageen
FieldComputer Science
Topicsemigroups and automata theory
Canadian institutionsWestern University
Fundersnot available
KeywordsTerminal and nonterminal symbolsSymbol (formal)Context-free grammarContext-sensitive grammarComputer scienceTree-adjoining grammarContext (archaeology)GrammarMildly context-sensitive grammar formalismIndexed grammarExtended Affix GrammarMathematicsCombinatory categorial grammarRule-based machine translationAlgorithmNatural language processingArtificial intelligenceGenerative grammarProgramming languageLinguisticsPhrase structure rules

Abstract

fetched live from OpenAlex

A set of transformations is presented that will convert an arbitrary context-free grammar to six of the normal forms for which the right hand side of any production has at most two occurrences of nonterminal symbols. These transformations form the basis of a meta-normal form algorithm for context-free grammars. The algorithm takes as input an arbitrary context-free grammar and a target normal form, expressed as an extended two-symbol grammar form, and converts the grammar to that normal form. The number of nonterminals and productions in the output grammars of each of the base transformations is minimal.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0010.001
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 head0.009
GPT teacher head0.196
Teacher spread0.187 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2004
Admission routes1
Has abstractyes

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