Data · dataset · 2024
POS-tagging model: Flair
Listed in Researchdata.se
Models Flair is a powerful NLP library.
Description
We provide two Flair models for Swedish part-of-speech tagging. flair_eval is trained on SUC3 with Talbanken_SBX_dev as dev set. The advantage of this model is that it can be evaluated, using Talbanken_SBX_test or SIC2.
The evaluation results are reported in the table below. Test set Exact match POS MSD Talbanken_SBX_test 0.978 0.987 0.990 SIC2 0.926 0.940 0.964 Read more about the evaluation here. flair_full is trained on SUC3 + Talbanken_SBX_test + SIC2 with Talbanken_SBX_dev as dev set. We cannot evaluate the performance of this model, but we expect it to perform better than flair_eval, or at least not worse.
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Using the models on your own Download the model and follow the instructions from Flair. By default, Flair's own embeddings will be used (our experiments show that they provide the best results), but you may use other embeddings instead (or combine them). GPU is strongly recommended.
Links
Where it is published
- DOI doi.org/10.23695/4a7m-mk50 ↗
DOI / persistent id · from researchdata se
Catalogue records · 1
- OAI-PMH record api.researchdata.se/oai-pmh?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3A… ↗
metadata API · from researchdata se
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Humanities
- Inferred from text
- Tabular 65%
Provenance · 1 source records, 9 field assertions
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|---|---|---|---|
| Researchdata.se | oai:researchdata.se:doi-10-23695-4a7m-mk50/0 | 11 d ago | JSON v1 |
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| concepts[modality].local:modality:tabular | enrichment · researchdata se | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata se | connector:researchdata_se@1.0.0 | /metadata/dc/description |
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