Notice bibliographique
Résumé
This dataset is distributed under a Creative Commons Attribution Non Commercial 4.0 International license. Use for research purposes only! The dataset contains 13,171 variable double-object and prepositional datives extracted from the International Corpus of English series and the Corpus of Global web-based English sampling from nine national varieties of English: British English Canadian English New Zealand English Irish English Hong Kong English Philippine English Singapore English Indian English Jamaican English The dataframe contains the following columns: 1 TokenID: Unique identifier for the individual token 2 Variety: The variety from which the token is taken 3 Nativity: Native or non-native variety of English (L1 vs. L2) 4 Corpus: The corpus from which the token stems 5 Subcorpus: Combination of Corpus and Variety 6 FileID: ID of the corpus file in which the token was found. Format: VARIETY:FILENAME 7 TextID: ID of the corpus text in which the token was found. Individual files in ICE can have multiple texts. Format: VARIETY:FILENAME:TEXTNUMBER 8 LineID: ID of the line in the text in which the token sentence was found. Format: VARIETY:FILENAME:TEXTNUMBER:LINENUMBER 9 SpeakerID: ID of the speaker of the sentence. Speakers in spoken texts are indicated with capital letters. Authors of written texts have ID ‘A’. Format: VARIETY:FILENAME:TEXTNUMBER:SPEAKERID 10 UnitMarker: UnitMarker of the utterance in the text. Format UTTERANCE NUMBER:TEXTNUMBER:SPEAKERID 11 GenreFine: 14-level distinction: The 12-level ICE sub-register in which the token was found and the two levels in GloWbE (blog vs. general). Levels: See ICE documentation 12 GenreCoarse: 5-level distinction: The 4-level ICE register in which the token was found and GloWbE (online = 1 level). Levels: See ICE documentation 13 Mode: The mode (‘spoken’, ‘written’) of the token. 14 Register: The 4-level Register along two axes – spoken vs. written / informal vs. formal 15 PriorContextPlain: The plain text version of the 100 words preceding the dative token. 16 PriorContextTag: The POS-tagged version of the 100 words preceding the dative token. 17 SentencePlain: The plain text version of the sentence containing the dative token. 18 SentenceTag: The POS-tagged version of the sentence containing the dative token. 19 WholeConstructionPlain: The plain text version of the VP containing the dative token (i.e. verb + object + object). 20 WholeConstructionTag: The POS-tagged version of the VP containing the dative token. 21 Verb: The lemma of the verbal head (give in gave it some thought) 22 VerbForm: The verb form of the verbal head (gave in gave it some thought) 23 RecipientShort: The short plain text version of the recipient without hesitations or repetitions 24 ThemeShort: The short plain text version of the theme without hesitations or repetitions 25 RecipientLong: The long plain text version of the recipient with hesitations or repetitions 26 ThemeLong: The long plain text version of the theme with hesitations or repetitions 27 RecHeadPlain: The plain text version of the recipient head 28 RecHeadTag: The POS-tagged version of the recipient head 29 RecHeadLemma: The lemma of the recipient head 30 ThemeHeadPlain: The plain text version of the theme head 31 ThemeHeadTag: The POS-tagged version of the theme head 32 ThemeHeadLemma: The lemma of the theme head 33 VerbThemeLemma: Combination of the verb lemma and the theme head. Format: VERB_THEME 34 VerbSense: Semantics of the verb based on the whole construction combined with the verb lemma. Format: VERB.VERBSEMANTICS 35 VerbSemantics: 5-level distinction of verb semantics (‘a’, ‘t’, ‘p’, ‘f’, ‘c’). 36 Resp: The variant order. Levels: ‘do’ (=ditransitive), ‘pd’ (=prepositional) 37 RecAnimacy: 6-level distinction of recipient animacy following previous research: human (a1) > animal (a2) > collective (c) > locative (l) > temporal (t) > inanimate (i) 38 ThemeAnimacy: 6-level distinction of theme animacy following previous research: human (a1) > animal (a2) > collective (c) > locative (l) > temporal (t) > inanimate (i) 39 RecWordLth: Length of recipient NP in words 40 RecLetterLth: Length of recipient NP in orthographic characters 41 ThemeWordLth: Length of theme NP in words 42 ThemeLetterLth: Length of theme NP in orthographic characters 43 RecComplexity 15-level distinction of recipient complexity indicating type and number of posthead dependents, restricted to the ICE components. (GloWbE components make simplified distinction between ‘simple’ and ‘complex’). Levels: ‘s’ = simple (no postmodifications), ‘co’ = coordinated, ‘ge’ = general extender, ‘gn’ = genitive, ‘postad’ = postmodifying adverbial/adjective, ‘pp’ = modifying prepositional phrase, ‘appnom’ = nominal apposition, ‘rc’ = relative clause, ‘cp’ = complement clause, ‘advc’ = adverbial clause, ‘nonfin’ = nonfinite clause, ‘tpp’ = two nominal posthead dependents, ‘tvp’ = two posthead dependents involving at least one VP, ‘mpp’ = more than two nominal posthead dependents, ‘mvp’ = more than two posthead dependents involving at least one VP 44 ThemeComplexity 15-level distinction of theme complexity indicating type and number of posthead dependents, restricted to the ICE components. (GloWbE components make simplified distinction between ‘simple’ and ‘complex’). Levels: ‘s’ = simple (no postmodifications), ‘co’ = coordinated, ‘ge’ = general extender, ‘gn’ = genitive, ‘postad’ = postmodifying adverbial/adjective, ‘pp’ = modifying prepositional phrase, ‘appnom’ = nominal apposition, ‘rc’ = relative clause, ‘cp’ = complement clause, ‘advc’ = adverbial clause, ‘nonfin’ = nonfinite clause, ‘tpp’ = two nominal posthead dependents, ‘tvp’ = two posthead dependents involving at least one VP, ‘mpp’ = more than two nominal posthead dependents, ‘mvp’ = more than two posthead dependents involving at least one VP 45 RecNPExprType: Syntactic category of the recipient NP Levels: ‘dem’ = bare demonstrative; ‘nc’ = common noun; ‘np’ = proper noun; ‘pprn’ = personal pronoun; ‘iprn’ = impersonal pronoun; ‘rprn’ = reflexive pronoun; ‘vp’ = gerund (-ing) NP; ‘wh’ = NP headed by wh- word 46 ThemeNPExprType: Syntactic category of the theme NP Levels: ‘dem’ = bare demonstrative; ‘nc’ = common noun; ‘np’ = proper noun; ‘pprn’ = personal pronoun; ‘iprn’ = impersonal pronoun; ‘rprn’ = reflexive pronoun; ‘vp’ = gerund (-ing) NP; ‘wh’ = NP headed by wh- word 47 RecGivenness: Givenness of the recipient NP. Levels: ‘given’, ‘new’ 48 ThemeGivenness: Givenness of the theme NP. Levels: ‘given’, ‘new’ 49 RecDefiniteness: Definiteness of the recipient NP. Levels: ‘def’, ‘indef’ 50 ThemeDefiniteness: Definiteness of the theme NP. Levels: ‘def’, ‘indef’ 51 RecBinComplexity: Binary predictor of recipient complexity indicating following postmodifications after the head noun. Levels: ‘simple’, ‘complex’ 52 ThemeBinComplexity: Binary predictor of theme complexity indicating following postmodifications after the head noun. Levels: ‘simple’, ‘complex’ 53 RecPerson: Person of recipient. Levels: ‘local’, ‘non-local’ 54 ThemeConcreteness: Concreteness of theme based on verb semantics. Levels: ‘concrete’, ‘non-concrete’ 55 TypeTokenRatio: Type-token ratio of the 100 word context surrounding the token 56 RecHeadFreq: Frequency of recipient head lemma in GloWbE 57 ThemeHeadFreq: Frequency of theme head lemma in GloWbE 58 RecThematicity: Normalized frequency of recipient head lemma in its text (per 2000 words) 59 ThemeThematicity: Normalized frequency of theme head lemma in its text (per 2000 words) 60 PrimeType: The response type of the preceding dative token, if any. Levels: ‘do, ‘pd, ‘NA’ 61 Persistence: Indicates whether preceding dative token, if any, is the same or not. Levels: ‘none’, ‘yes’, ‘no’ 62 SameUtterance: Indicates whether the preceding dative token occurred in the same utterance or not. Necessary for manual coding of persistence. 63 DistanceToPrevious: Number of utterances between current and preceding dative token. ‘None’ if no preceding dative token. 64 RecPron: Binary factor of recipient pronominality. Levels: ‘pron’, ‘non-pron’ 65 ThemePron: Binary factor of theme pronominality: Levels: ‘pron’, ‘non-pron’ 66 RecBinAnimacy: Binary factor of recipient animacy. Levels of RecAnimacy conflated to: ‘animate’, ‘inanimate’ 67 ThemeBinAnimacy: Binary factor of theme animacy. Levels of ThemeAnimacy conflated to: ‘animate’, ‘inanimate’ 68 logRecLetterLth: Natural logarithm of recipient length in orthographic characters 69 logThemeLetterLth: Natural logarithm of theme length in orthographic characters 70 WeightRatio: Ratio of object lengths: Recipient length in characters divided by theme length in characters 71 logWeightRatio: Natural logarithm of weight ratio 72 PrimeTypePruned: The variant of the preceding dative token within the previous 10 utterances. Levels: ‘none’, ‘do’, ‘pd’ 73 NumDistanceToPrevious: Numeric distance to previous token (for calculations in R) 74 PersistencePruned: Indicates whether the preceding token within the previous 10 utterances is the same as the current token. Levels: ‘none’, ‘yes’, ‘no’ 75-82 z.__________: Numeric predictor centered around the mean and scaled by two standard deviations. 83 Variety.Sum: Column used for sum coding in modeling process
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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,054 | 0,096 |
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 ».