browndw/en_docusco_spacy_cd_trf

English pipeline for part-of-speech and rhetorical tagging using a smaller 'common dictionary'.

Feature	Description
Name	en_docusco_spacy_cd_trf
Version	1.3
spaCy	>=3.7.4,<3.8.0
Default Pipeline	transformer, tagger, ner
Components	transformer, tagger, ner
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	n/a
License	MIT
Author	David Brown

Label Scheme

View label scheme (289 labels for 2 components)

Component	Labels
tagger	APPGE, AT, AT1, BCL21, BCL22, CC, CCB, CS, CS21, CS22, CS31, CS32, CS33, CS41, CS42, CS43, CS44, CSA, CSN, CST, CSW, CSW31, CSW32, CSW33, DA, DA1, DA2, DAR, DAT, DB, DB2, DD, DD1, DD2, DDQ, DDQGE, DDQGE31, DDQGE32, DDQGE33, DDQV, DDQV31, DDQV32, DDQV33, EX, FO, FU, FW, GE, IF, II, II21, II22, II31, II32, II33, II41, II42, II43, II44, IO, IW, JJ, JJ21, JJ22, JJ31, JJ32, JJ33, JJ41, JJ42, JJ43, JJ44, JJR, JJT, JK, MC, MC1, MC2, MC221, MC222, MCMC, MD, MF, ND1, NN, NN1, NN121, NN122, NN131, NN132, NN133, NN141, NN142, NN143, NN144, NN2, NN21, NN22, NN221, NN222, NN31, NN32, NN33, NNA, NNB, NNL1, NNL2, NNO, NNO2, NNT1, NNT131, NNT132, NNT133, NNT2, NNU, NNU1, NNU2, NNU21, NNU22, NNU221, NNU222, NP, NP1, NP2, NPD1, NPD2, NPM1, NPM2, PN, PN1, PN121, PN122, PN21, PN22, PNQO, PNQS, PNQS31, PNQS32, PNQS33, PNQV, PNQV31, PNQV32, PNQV33, PNX1, PPGE, PPH1, PPHO1, PPHO2, PPHS1, PPHS2, PPIO1, PPIO2, PPIS1, PPIS2, PPX1, PPX121, PPX122, PPX2, PPX221, PPX222, PPY, RA, RA21, RA22, REX, REX21, REX22, REX41, REX42, REX43, REX44, RG, RG21, RG22, RG41, RG42, RG43, RG44, RGQ, RGQV, RGQV31, RGQV32, RGQV33, RGR, RGT, RL, RL21, RL22, RL31, RL32, RL33, RP, RPK, RR, RR21, RR22, RR31, RR32, RR33, RR41, RR42, RR43, RR44, RR51, RR52, RR53, RR54, RR55, RRQ, RRQV, RRQV31, RRQV32, RRQV33, RRR, RRT, RT, RT21, RT22, RT31, RT32, RT33, RT41, RT42, RT43, RT44, TO, UH, UH21, UH22, UH31, UH32, UH33, VB0, VBDR, VBDZ, VBG, VBI, VBM, VBN, VBR, VBZ, VD0, VDD, VDG, VDI, VDN, VDZ, VH0, VHD, VHG, VHI, VHN, VHZ, VM, VM21, VM22, VMK, VV0, VVD, VVG, VVGK, VVI, VVN, VVNK, VVZ, XX, Y, ZZ1, ZZ2, ZZ221, ZZ222
ner	ActorsAbstractions, ActorsFirstPerson, ActorsPeople, ActorsPublicEntities, CitationAuthority, CitationControversy, CitationNeutral, ConfidenceHedged, ConfidenceHigh, OrganizationNarrative, OrganizationReasoning, PlanningFuture, PlanningStrategy, SentimentNegative, SentimentPositive, SignpostingAcademicWritingMoves, SignpostingMetadiscourse, StanceEmphatic, StanceModerated

Accuracy

Type	Score
TAG_ACC	98.60
ENTS_F	89.86
ENTS_P	89.76
ENTS_R	89.96
TRANSFORMER_LOSS	4671131.21
TAGGER_LOSS	1405830.04
NER_LOSS	4168254.47