README.md

metadata

tags:
  - spacy
  - token-classification
language:
  - en
license: mit
model-index:
  - name: en_docusco_spacy_cd
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.7896141572
          - name: NER Recall
            type: recall
            value: 0.7757775447
          - name: NER F Score
            type: f_score
            value: 0.7826346995
      - task:
          name: TAG
          type: token-classification
        metrics:
          - name: TAG (XPOS) Accuracy
            type: accuracy
            value: 0.9734866573

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

Feature	Description
Name	en_docusco_spacy_cd
Version	1.2
spaCy	>=3.5.0,<3.6.0
Default Pipeline	tok2vec, tagger, ner
Components	tok2vec, tagger, ner
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	n/a
License	MIT
Author	David Brown

Label Scheme

View label scheme (270 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, 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, 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, NN231, NN232, NN233, NN31, NN33, NNA, NNB, NNL1, NNL2, NNO, NNO2, NNT1, NNT2, NNU, NNU1, NNU2, NNU21, NNU22, NP, NP1, NP2, NPD1, NPD2, NPM1, NPM2, PN, PN1, PN121, PN122, PN21, PN22, PNQO, PNQS, PNQS31, PNQS32, PNQS33, PNQV, 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, RGQ, RGQV, RGQV31, RGQV32, RGQV33, RGR, RGT, RL, RL21, RL22, 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, CitationHedged, CitationNeutral, ConfidenceHedged, ConfidenceHigh, OrganizationNarrative, OrganizationReasoning, PlanningFuture, PlanningStrategy, SentimentNegative, SentimentPositive, SignpostingAcademicWritingMoves, SignpostingMetadiscourse, StanceEmphatic, StanceModerated

Accuracy

Type	Score
TAG_ACC	97.35
ENTS_F	78.26
ENTS_P	78.96
ENTS_R	77.58
TOK2VEC_LOSS	5937424.94
TAGGER_LOSS	1136040.49
NER_LOSS	3941726.32