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Record W3207435583 · doi:10.1145/3156695.3122958

Packrats parse in packs

2017· article· en· W3207435583 on OpenAlexaff
Mario Blažević, Jacques Légaré

Bibliographic record

VenueACM SIGPLAN Notices · 2017
Typearticle
Languageen
FieldComputer Science
TopicLogic, programming, and type systems
Canadian institutionsMagna International (Canada)
Fundersnot available
KeywordsHaskellComputer scienceProgramming languageParsingRule-based machine translationSimple (philosophy)Functional programmingParsing expression grammarSet (abstract data type)GrammarRank (graph theory)Artificial intelligenceL-attributed grammarContext-free grammar

Abstract

fetched live from OpenAlex

We present a novel but remarkably simple formulation of formal language grammars in Haskell as functions mapping a record of pro- duction parsers to itself. Thus formulated grammars are first-class objects, composable and reusable. We also provide a simple parser implementation for them, based on an improved packrat algorithm. In order to make the grammar manipulation code reusable, we introduce a set of type classes mirroring the existing type classes from Haskell base library, but whose methods have rank-2 types.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.698

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 communication0.0010.001
Open science0.0030.001
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 head0.050
GPT teacher head0.292
Teacher spread0.243 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2017
Admission routes1
Has abstractyes

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