Notice bibliographique
Résumé
This is a wonderful book-and not just for people actively involved in machine translation.Anyone with an interest in the history of computational linguistics will find much to relish and learn from in this weighty collection of articles past.Lest we forget, MT was one of the first nonnumerical applications proposed for the digital computer following the Second World War, and its often tumultuous 50-year history has had a significant impact on the entire field of computational linguistics.Indeed, this very journal can trace its lineage back to the journal whose original title was Mechanical Translation.Though not a proper history of MT, Readings in Machine Translation is certainly a historical collection.The editors have sought to bring together in one volume "the 'classical' MT papers that researchers and students want, or should be persuaded, to read" (page xi) and that, alas, are often so difficult to find.For this alone, Nirenburg, Somers, and Wilks deserve our gratitude.The volume begins with the famous memorandum that Warren Weaver sent out to some 200 professional acquaintances in 1949, which is generally taken to mark the genesis of machine translation; and the most recent paper included dates back to the fourth MT Summit in 1993.The 36 articles that span the intervening period are said to constitute "MT's communal inheritance."By what criteria were the papers selected?The editors cite three: personal taste; the aforementioned problem of availability, which is certainly a real one, particularly in the case of some of the early classics; and historical significance, which is said to be the main criterion for inclusion in the volume.The articles selected by the editors are supposed to represent "the most important papers from the past 50 years" of MT (p.xi).Well, as criteria go, that certainly sets a high standard!And yet many of these articles seem to meet it with ease.In addition to Weaver's memorandum and a monumental state of the art published by Bar-Hillel in 1960, both of which absolutely must be read, there is a jewel of a piece written by Victor Yngve in 1957 that argues for what later became known as second-generation MT: systems that analyze the input text into an essentially syntactic intermediate representation that serves as the basis for transfer, rather than applying a bilingual dictionary directly to the input string, as first-generation systems did.There is Martin Kay's "The Proper Place of Men and Machines in Language Translation"-an MT classic if ever there was one-in which the author derides the pursuit of fully automatic MT, not as a legitimate goal of basic research, but as a strategy promising a short-term solution to the burgeoning demand for translation; in its place, Kay proposes a modest, incremental program of machine aids for human translation: "little steps for little feet."There is Makoto Nagao's 1984 paper that launched the entire example-based MT paradigm (still very much alive and kicking), as well as a stellar piece by Jan Landsbergen laying out the advantages for
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,004 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,290 | 0,231 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».