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EN
Nb Core News Sm
CPU-optimized Norwegian Bokmål processing pipeline, including token classification, dependency parsing, named entity recognition, etc.
Downloads 58
Release Time : 3/2/2022
Model Overview
This is a spaCy small Norwegian Bokmål processing model, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, etc., optimized for CPU usage.
Model Features
CPU Optimization
Specifically optimized for CPU usage, suitable for resource-limited environments
Comprehensive NLP Processing
Provides a complete natural language processing pipeline from tokenization to named entity recognition
High Accuracy
Excellent performance on Norwegian Bokmål tasks, such as a part-of-speech tagging accuracy of 96.74%
Model Capabilities
Tokenization
Part-of-speech tagging
Morphological analysis
Lemmatization
Dependency parsing
Named entity recognition
Sentence segmentation
Use Cases
Text Processing
News Analysis
Processing Norwegian Bokmål news texts to extract entities and syntactic structures
NER F-score reached 75.19%
Linguistic Research
Used for grammatical and morphological studies of Norwegian Bokmål
Morphological feature accuracy reached 95.32%
Information Extraction
Entity Recognition
Identifying entities such as person names, place names, and organization names from text
Supports recognition of 9 entity types
🚀 nb_core_news_sm
The Norwegian (Bokmål) pipeline optimized for CPU, designed for token - classification tasks.
🚀 Quick Start
The nb_core_news_sm is a Norwegian (Bokmål) pipeline optimized for CPU. For more details, please visit https://spacy.io/models/nb#nb_core_news_sm.
✨ Features
- Optimized for CPU, suitable for various token - classification tasks such as NER, TAG, POS, etc.
- It contains multiple components like
tok2vec,morphologizer,parser, etc., which can handle different aspects of text processing.
📚 Documentation
Model Information
| Property | Details |
|---|---|
| Model Type | nb_core_news_sm |
| Version | 3.7.0 |
| spaCy | >=3.7.0,<3.8.0 |
| Default Pipeline | tok2vec, morphologizer, parser, lemmatizer, attribute_ruler, ner |
| Components | tok2vec, morphologizer, parser, lemmatizer, senter, attribute_ruler, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | UD Norwegian Bokmaal v2.8 (Øvrelid, Lilja; Jørgensen, Fredrik; Hohle, Petter) NorNE: Norwegian Named Entities (commit: bd311de5) (Language Technology Group (University of Oslo)) |
| License | MIT |
| Author | Explosion |
Label Scheme
View label scheme (249 labels for 3 components)
| Component | Labels |
|---|---|
morphologizer |
Definite=Ind|Gender=Neut|Number=Sing|POS=NOUN, POS=CCONJ, Definite=Ind|Gender=Masc|Number=Sing|POS=NOUN, POS=SCONJ, Definite=Def|Gender=Masc|Number=Sing|POS=NOUN, Definite=Ind|Gender=Neut|Number=Plur|POS=NOUN, POS=PUNCT, Mood=Ind|POS=VERB|Tense=Past|VerbForm=Fin, POS=ADP, Gender=Masc|Number=Sing|POS=DET|PronType=Dem, Definite=Def|Degree=Pos|Number=Sing|POS=ADJ, POS=PROPN, POS=X, Mood=Ind|POS=VERB|Tense=Pres|VerbForm=Fin, Definite=Def|Gender=Neut|Number=Sing|POS=NOUN, POS=PRON|PronType=Rel, Mood=Ind|POS=AUX|Tense=Pres|VerbForm=Fin, Definite=Ind|Gender=Neut|Number=Sing|POS=ADJ|VerbForm=Part, Definite=Ind|Degree=Pos|Number=Sing|POS=ADJ, Definite=Ind|Gender=Fem|Number=Sing|POS=NOUN, Number=Plur|POS=ADJ|VerbForm=Part, Definite=Ind|Gender=Fem|Number=Plur|POS=NOUN, POS=ADV, Gender=Neut|Number=Sing|POS=PRON|Person=3|PronType=Prs, Definite=Ind|Number=Sing|POS=ADJ|VerbForm=Part, POS=VERB|VerbForm=Part, Definite=Ind|Gender=Masc|Number=Plur|POS=NOUN, Definite=Ind|Degree=Pos|Gender=Neut|Number=Sing|POS=ADJ, Degree=Pos|Number=Plur|POS=ADJ, NumType=Card|Number=Plur|POS=NUM, Definite=Def|Gender=Masc|Number=Plur|POS=NOUN, Case=Acc|POS=PRON|PronType=Prs|Reflex=Yes, Case=Gen|Definite=Ind|Gender=Neut|Number=Sing|POS=NOUN, POS=PART, POS=VERB|VerbForm=Inf, Case=Nom|Number=Plur|POS=PRON|Person=3|PronType=Prs, Mood=Ind|POS=AUX|Tense=Past|VerbForm=Fin, Gender=Fem|POS=PROPN, POS=NOUN, Gender=Masc|POS=PROPN, Gender=Neut|Number=Sing|POS=DET|PronType=Dem, Gender=Masc|Number=Sing|POS=DET|PronType=Art, Case=Gen|Definite=Def|Gender=Masc|Number=Sing|POS=NOUN, Abbr=Yes|POS=PROPN, POS=PART|Polarity=Neg, Number=Plur|POS=PRON|Poss=Yes|PronType=Prs, Case=Gen|Definite=Ind|Gender=Neut|Number=Plur|POS=NOUN, Case=Gen|POS=PROPN, Gender=Fem|Number=Sing|POS=DET|PronType=Dem, Gender=Masc|Number=Sing|POS=PRON|Poss=Yes|PronType=Prs, Definite=Def|Degree=Sup|POS=ADJ, Case=Gen|Gender=Fem|POS=PROPN, Number=Plur|POS=DET|PronType=Dem, Case=Gen|Definite=Def|Gender=Neut|Number=Sing|POS=NOUN, Definite=Ind|Degree=Sup|POS=ADJ, Definite=Def|Gender=Fem|Number=Plur|POS=NOUN, Gender=Neut|POS=PROPN, Number=Plur|POS=DET|PronType=Int, Definite=Def|Gender=Neut|Number=Plur|POS=NOUN, Definite=Def|POS=DET|PronType=Dem, Gender=Neut|Number=Sing|POS=DET|PronType=Art, Mood=Ind|POS=VERB|Tense=Pres|VerbForm=Fin|Voice=Pass, Abbr=Yes|Case=Gen|POS=PROPN, Animacy=Hum|Case=Nom|Gender=Masc|Number=Sing|POS=PRON|Person=3|PronType=Prs, Degree=Cmp|POS=ADJ, POS=ADJ|VerbForm=Part, Gender=Neut|Number=Sing|POS=PRON|Poss=Yes|PronType=Prs, Abbr=Yes|POS=ADP, Definite=Ind|Gender=Neut|Number=Sing|POS=DET|PronType=Prs, Case=Gen|Definite=Def|Gender=Neut|Number=Plur|POS=NOUN, POS=AUX|VerbForm=Part, POS=PRON|PronType=Int, Gender=Fem|Number=Sing|POS=PRON|Poss=Yes|PronType=Prs, Number=Plur|POS=PRON|Person=3|PronType=Ind,Prs, Number=Plur|POS=DET|PronType=Ind, Degree=Pos|POS=ADJ, Animacy=Hum|Case=Nom|Number=Plur|POS=PRON|Person=1|PronType=Prs, POS=VERB|VerbForm=Inf|Voice=Pass, Definite=Ind|Gender=Fem|Number=Sing|POS=DET|PronType=Dem, Gender=Neut|Number=Sing|POS=DET|PronType=Ind, Animacy=Hum|Case=Acc|Gender=Masc|Number=Sing|POS=PRON|Person=3|PronType=Prs, Animacy=Hum|Case=Nom|Number=Sing|POS=PRON|Person=1|PronType=Prs, Number=Plur|POS=DET|Polarity=Neg|PronType=Neg, NumType=Card|POS=NUM, Gender=Masc|Number=Sing|POS=DET|PronType=Ind, POS=DET|PronType=Prs, Gender=Fem|Number=Sing|POS=DET|PronType=Ind, Case=Gen|Gender=Neut|POS=PROPN, Gender=Masc|Number=Sing|POS=DET|Polarity=Neg|PronType=Neg, Definite=Def|Number=Sing|POS=ADJ|VerbForm=Part, Gender=Fem,Masc|Number=Sing|POS=PRON|Person=3|PronType=Prs, POS=AUX|VerbForm=Inf, Case=Acc|Number=Plur|POS=PRON|Person=3|PronType=Prs, Case=Gen|Degree=Pos|Number=Plur|POS=ADJ, Number=Plur|POS=DET|PronType=Tot, Case=Gen|Gender=Masc|Number=Sing|POS=DET|PronType=Dem, Number=Plur|POS=DET|PronType=Prs, POS=SYM, Gender=Neut|NumType=Card|Number=Sing|POS=NUM, Animacy=Hum|Case=Nom|Number=Sing|POS=PRON|PronType=Prs, Definite=Ind|Gender=Masc|Number=Sing|POS=DET|PronType=Prs, Case=Gen|Definite=Ind|Gender=Masc|Number=Sing|POS=NOUN, Abbr=Yes|POS=ADV, Definite=Ind|Gender=Neut|Number=Sing|POS=DET|PronType=Dem, Gender=Masc|Number=Sing|POS=DET|PronType=Tot, Definite=Def|POS=DET|PronType=Prs, Animacy=Hum|Case=Nom|Gender=Fem|Number=Sing|POS=PRON|Person=3|PronType=Prs, Gender=Neut|POS=NOUN, Gender=Neut|Number=Sing|POS=DET|PronType=Int, Definite=Def|NumType=Card|POS=NUM, Mood=Imp|POS=VERB|VerbForm=Fin, Definite=Ind|Number=Plur|POS=NOUN, Gender=Neut|Number=Sing|POS=DET|PronType=Tot, Gender=Fem|Number=Sing|POS=DET|PronType=Tot, Animacy=Hum|Case=Acc|Number=Plur|POS=PRON|Person=1|PronType=Prs, Gender=Fem,Masc|Number=Sing|POS=PRON|Person=3|Polarity=Neg|PronType=Neg,Prs, Number=Plur|POS=PRON|Person=3|Polarity=Neg|PronType=Neg,Prs, Definite=Def|NumType=Card|Number=Sing|POS=NUM, Gender=Masc|NumType=Card|Number=Sing|POS=NUM, Definite=Ind|Gender=Masc|Number=Sing|POS=DET|PronType=Dem, Case=Gen|Definite=Def|Gender=Fem|Number=Plur|POS=NOUN, Case=Gen|Gender=Neut|Number=Sing|POS=DET|PronType=Dem, POS=SPACE, Animacy=Hum|Number=Sing|POS=PRON|PronType=Art,Prs, Mood=Imp|POS=AUX|VerbForm=Fin, Number=Plur|POS=PRON|Person=3|PronType=Prs,Tot, Number=Plur|POS=ADJ, Gender=Masc|POS=NOUN, Abbr=Yes|POS=NOUN, Case=Gen|Definite=Ind|Gender=Masc|Number=Plur|POS=NOUN, Gender=Neut|Number=Sing|POS=PRON|Person=3|PronType=Ind,Prs, POS=INTJ, Animacy=Hum|Case=Nom|Number=Sing|POS=PRON|Person=2|PronType=Prs, Animacy=Hum|Case=Acc|Number=Sing|POS=PRON|Person=1|PronType=Prs, Case=Gen|Definite=Def|Gender=Masc|Number=Plur|POS=NOUN, POS=ADJ, Animacy=Hum|Case=Acc|Gender=Fem|Number=Sing|POS=PRON|Person=3|PronType=Prs, Animacy=Hum|Case=Acc|Number=Sing|POS=PRON|Person=2|PronType=Prs, Definite=Def|Gender=Fem|Number=Sing|POS=NOUN, Number=Sing|POS=PRON|Polarity=Neg|PronType=Neg, Case=Gen|POS=NOUN, Definite=Ind|Number=Sing|POS=ADJ, Case=Gen|Gender=Masc|POS=PROPN, Animacy=Hum|Number=Plur|POS=PRON|PronType=Rcp, Case=Gen|Definite=Ind|Gender=Fem|Number=Sing|POS=NOUN, Number=Plur|POS=PRON|Person=3|PronType=Prs, Gender=Fem,Masc|Number=Sing|POS=PRON|Person=3|PronType=Ind,Prs, Definite=Ind|Gender=Fem|Number=Sing|POS=DET|PronType=Prs, Case=Gen|Definite=Def|Gender=Fem|Number=Sing|POS=NOUN, Gender=Fem|Number=Sing|POS=DET|PronType=Art, Case=Gen|Definite=Def|Degree=Pos|Number=Sing|POS=ADJ, Gender=Masc|Number=Sing|POS=DET|PronType=Int, NumType=Card|Number=Sing|POS=NUM, Animacy=Hum|Case=Acc|Number=Plur|POS=PRON|Person=2|PronType=Prs, Animacy=Hum|Case=Nom|Number=Plur|POS=PRON|Person=2|PronType=Prs, Case=Gen|Definite=Ind|Degree=Pos|Gender=Neut|Number=Sing|POS=ADJ, Degree=Sup|POS=ADJ, Animacy=Hum|POS=PRON|PronType=Int, POS=DET|PronType=Ind, Definite=Def|Number=Sing|POS=DET|PronType=Dem, Gender=Fem|POS=NOUN, Case=Gen|Number=Plur|POS=DET|PronType=Dem, Gender=Fem,Masc|Number=Sing|POS=PRON|Person=3|PronType=Prs,Tot, Case=Gen|Definite=Ind|Gender=Fem|Number=Plur|POS=NOUN, Gender=Neut|Number=Sing|POS=DET|Polarity=Neg|PronType=Neg, Number=Plur|POS=NOUN, POS=PRON|PronType=Prs, Case=Gen|Definite=Ind|Degree=Pos|Number=Sing|POS=ADJ, Definite=Ind|Number=Sing|POS=VERB|VerbForm=Part, Case=Gen|Definite=Def|Number=Sing|POS=ADJ|VerbForm=Part, Mood=Ind|POS=VERB|Tense=Past|VerbForm=Fin|Voice=Pass, Gender=Neut|Number=Sing|POS=DET|PronType=Dem,Ind, Animacy=Hum|POS=PRON|Poss=Yes|PronType=Int, Abbr=Yes|POS=ADJ, Case=Gen|Gender=Masc|Number=Sing|POS=DET|PronType=Art, Abbr=Yes|Definite=Def,Ind|Gender=Masc|Number=Sing|POS=NOUN, Case=Gen|Gender=Fem|Number=Sing|POS=DET|PronType=Dem, Number=Plur|POS=PRON|Poss=Yes|PronType=Rcp, Definite=Ind|Degree=Pos|POS=ADJ, Number=Plur|POS=DET|PronType=Art, Case=Gen|NumType=Card|Number=Plur|POS=NUM, Abbr=Yes|Definite=Def,Ind|Gender=Neut|Number=Plur,Sing|POS=NOUN, Case=Gen|Number=Plur|POS=DET|PronType=Tot, Abbr=Yes|Definite=Def,Ind|Gender=Masc|Number=Plur,Sing|POS=NOUN, Gender=Fem|Number=Sing|POS=DET|PronType=Int, Definite=Ind|Gender=Neut|Number=Sing|POS=ADJ, Case=Gen|Definite=Ind|Gender=Masc|Number=Sing|POS=DET|PronType=Dem, Gender=Fem|Number=Sing|POS=DET|PronType=Prs, Animacy=Hum|Case=Gen,Nom|Number=Sing|POS=PRON|PronType=Art,Prs, Definite=Def|Degree=Pos|Gender=Masc|Number=Sing|POS=ADJ, Animacy=Hum|Case=Gen|Number=Sing|POS=PRON|PronType=Art,Prs, Gender=Fem|NumType=Card|Number=Sing|POS=NUM, Definite=Ind|Gender=Masc|POS=NOUN, Definite=Def|Number=Plur|POS=NOUN, Number=Sing|POS=ADJ|VerbForm=Part, Definite=Ind|Gender=Masc|Number=Sing|POS=ADJ|VerbForm=Part, Abbr=Yes|Gender=Masc|POS=NOUN, Abbr=Yes|Case=Gen|POS=NOUN, Abbr=Yes|Mood=Ind|POS=VERB|Tense=Pres|VerbForm=Fin, Abbr=Yes|Degree=Pos|POS=ADJ, Case=Gen|Gender=Fem|POS=NOUN, Case=Gen|Degree=Cmp|POS=ADJ, Definite=Ind|Degree=Pos|Gender=Masc|Number=Sing|POS=ADJ, Gender=Masc|Number=Sing|POS=NOUN |
parser |
ROOT, acl, acl:cleft, acl:relcl, advcl, advmod, amod, appos, aux, aux:pass, case, cc, ccomp, compound, compound:prt, conj, cop, csubj, dep, det, discourse, expl, flat:foreign, flat:name, iobj, mark, nmod, nsubj, nsubj:pass, nummod, obj, obl, orphan, parataxis, punct, xcomp |
ner |
DRV, EVT, GPE_LOC, GPE_ORG, LOC, MISC, ORG, PER, PROD |
Accuracy
| Type | Score |
|---|---|
TOKEN_ACC |
99.81 |
TOKEN_P |
99.71 |
TOKEN_R |
99.53 |
TOKEN_F |
99.62 |
POS_ACC |
96.74 |
MORPH_ACC |
95.32 |
MORPH_MICRO_P |
97.02 |
MORPH_MICRO_R |
96.07 |
🔧 Technical Details
The model is a Norwegian (Bokmål) pipeline optimized for CPU. It consists of multiple components, each with its own specific functions:
- tok2vec: Converts tokens into vector representations.
- morphologizer: Analyzes the morphological features of words.
- parser: Parses the syntactic structure of sentences.
- lemmatizer: Reduces words to their base or dictionary form.
- senter: Identifies sentence boundaries.
- ner: Performs named - entity recognition.
- attribute_ruler: Applies custom rules for attribute assignment.
The model has been trained on specific datasets, including UD Norwegian Bokmaal v2.8 and NorNE: Norwegian Named Entities (commit: bd311de5).
📄 License
This project is licensed under the MIT license.
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