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Record W3172079241

The lemmatisation of Old English comparative adverbs.

2020· article· es· W3172079241 on OpenAlexaboutno aff
Yosra Hamdoun Bghiyel

Bibliographic record

VenueRAEL: revista electrónica de lingüística aplicada · 2020
Typearticle
Languagees
FieldArts and Humanities
TopicLexicography and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsLemma (botany)HumanitiesPoetryArtificial intelligenceLexicographyNatural language processingHistoryComputer scienceArtPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

AbstractThis paper aims at presenting a pilot study in the lemmatisation of Old English superlatives. This research is a further contribution to the lemmatisation methodology implemented in the OE verbal classes. The adverbs graded for the comparative have been chosen for this study. The data have been retrieved from The York-Toronto-Helsinki Parsed Corpus of Old English Prose and The York-Toronto-Helsinki Parsed Corpus of Old English Poetry. The starting point of this study is the automatic extraction of the forms morphologically tagged with the ADVR label (comparative adverbs). Secondly, the resulting forms are manually assigned the lemma provided by the lexical database of Old English Nerthus. Thirdly, the results are compared with Seelig (1930) and with the Dictionary of Old English in order to verify the lemma assignment and disambiguate doubtful cases. The conclusions insist on the applicability of the lemmatisation method to all non-verbal categories of Old English.Keywords: Old English; corpus linguistics; lexicography; lemmatisation; comparative adverbs. ResumenEste articulo presenta un estudio piloto sobre la lematizacion de los adverbios comparativos del ingles antiguo. Esta investigacion contribuye a la metodologia previamente implementada en la lematizacion de las clases verbales. Los corpus The York-Toronto-Helsinki Parsed Corpus of Old English Prose y The York-Toronto-Helsinki Parsed Corpus of Old English Poetry han proveido las formas flexivas a lematizar. El punto de partida de este estudio es la extraccion automatica de las formas morfologicamente etiquetadas con la etiqueta ADVR (adverbios comparativos). En segundo lugar, se ha asignado un lema de la base lexica Nerthus a cada forma flexiva. En tercer lugar, los resultados han sido contrastados con Seelig (1930) y el Dictionary of Old English para verificar la asignacion de lemas y desambiguar casos dudosos. Las conclusiones insisten en la aplicabilidad de este metodo de lematizacion al resto de categorias no verbales de ingles antiguo.Palabras clave: ingles antiguo, adverbios comparativos, linguistica de corpus, lematizacion.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.259
Teacher spread0.233 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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Same venueRAEL: revista electrónica de lingüística aplicadaSame topicLexicography and Language StudiesFrench-language works237,207