Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".