---
language:
- nb
license: cc-by-sa-3.0
task_categories:
- text-generation
pretty_name: NPSC Ortho Morphcoded Clean
tags:
- norwegian
- morphology
- text2text-generation
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: eval
    path: data/eval-*
  - split: eval_clean
    path: data/eval_clean-*
  - split: test
    path: data/test-*
  - split: test_clean
    path: data/test_clean-*
---

# NPSC Ortho Morphcoded Clean

This is a consensus-filtered derivative of
[NbAiLab/NPSC_orto_morphcoded](https://huggingface.co/datasets/NbAiLab/NPSC_orto_morphcoded) at revision
'c0a5864ffde32ca05a683652b54282ee785ca16d'. It retains the original id, source, and target schema and
the original source text.

## Cleaning method

A T5Gemma 2 1B model fine-tuned on the source dataset generated one prediction
for every row. Exact model/target agreements were retained. Every disagreement
was shown to two isolated language-model reviewers with the source plus
randomized candidates A and B; neither reviewer saw candidate provenance or the
other review. Each reviewer could select only A, B, or None.

A disagreement was retained only when both reviewers independently selected
the same non-None candidate after candidate randomization was decoded. Every
other disagreement was dropped. A unanimous candidate was also dropped if it
failed AltMorph syntax or exact source-recoverability checks. Selected targets
were canonicalized to case-insensitive alphabetical alternative order.

The automated reviewers are a quality-control heuristic, not human linguistic
annotation. Agreement between the generator, model, or reviewers does not
prove that every retained alternative is authoritative or context-preserving.

| Source split | Input | Model/target agreement | GT selected | Model selected | Dropped |
| --- | ---: | ---: | ---: | ---: | ---: |
| train | 62,541 | 61,346 | 566 | 482 | 147 |
| validation | 1,000 | 924 | 45 | 22 | 9 |
| test | 1,000 | 934 | 38 | 21 | 7 |

## Published splits

train is the cleaned original training split. eval and test preserve all
original evaluation rows and labels for direct comparability. eval_clean and
test_clean contain only rows retained by the consensus-cleaning procedure,
with the selected target.

| Split | Rows | Source differs from target |
| --- | ---: | ---: |
| train | 62,394 | 35,830 |
| eval | 1,000 | 581 |
| eval_clean | 991 | 582 |
| test | 1,000 | 563 |
| test_clean | 993 | 561 |

## Split overlap

Split IDs are disjoint, but the upstream random split contains repeated rows.
The following counts are measured against train after cleaning. Exact repeated
source/target pairs can make evaluation optimistic and must not be interpreted
as independent generalization.

| Split | ID overlap rows | Exact source/target overlap rows | Unique overlapping sources |
| --- | ---: | ---: | ---: |
| eval | 0 | 105 | 84 |
| eval_clean | 0 | 105 | 84 |
| test | 0 | 99 | 76 |
| test_clean | 0 | 99 | 76 |

## Fields

| Field | Meaning |
| --- | --- |
| id | Original NPSC sentence ID as a string. |
| source | Norwegian parliamentary transcript text. |
| target | Source-preserving AltMorph encoding with alphabetically ordered alternatives. |

## Provenance

- Generated: 2026-08-29T00:00:23.289993+00:00
- Source dataset: 'NbAiLab/NPSC_orto_morphcoded'
- Source revision: 'c0a5864ffde32ca05a683652b54282ee785ca16d'
- Cleaning model: google/t5gemma-2-1b-1b, fine-tuned run
  t5gemma2-1b-altmorph-v2-alpha
- Reviewers: two independently isolated automated language-model agents
- Decision choices: A, B, or None
- Retention rule for disagreements: unanimous A or unanimous B only

The source dataset card documents NPSC and AltMorph generation in detail,
including HumIT, Ordbank, North-T5, source licensing, and attribution. This
derivative uses CC BY-SA 3.0 conservatively and preserves those attribution
requirements.

Please credit:

- the National Library of Norway and NPSC dataset maintainers;
- the University of Oslo HumIT team and Humit-Oslo/humit-tagger-large;
- the University of Bergen Ordbank service;
- the North-T5 authors and north/t5_base_NCC;
- the AltMorph authors; and
- Google and the T5Gemma authors for the cleaning model.

The upstream parliamentary transcriptions are described as CC0, while the
Hugging Face curation and this derivative use CC BY-SA 3.0.

## Limitations

The dataset remains automatically generated silver data. In-sample predictions
on the training split can reflect memorization, and shared model/target errors
survive automatic agreement filtering. Agent judgments can also be correlated
or linguistically wrong. Use eval/test for comparison with the original silver
labels and eval_clean/test_clean for the stricter retained subset. Fresh human
or linguist evaluation is recommended for consequential use.