Publish consensus-cleaned AltMorph dataset

README.md

@@ -0,0 +1,116 @@
+---
+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 |
+
+## 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: 2026-08-28T22:51:33.047771+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.

data/eval-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:98be2f3d61c7c5c75257bdaaa0439eee7a6bdbde39d042558cfd87c07c58a1e6
+size 109897

data/eval_clean-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ba9df88c9d1b015e2d27213962b300ca4acd9f413109c066cfb531d691fd7cb0
+size 108713

data/test-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a699dc2dfa2fb02a4b2c9cfa9a791226b65320a8fb5bbd406980a977a9e5d70f
+size 109398

data/test_clean-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:10d8476b401446ad2e9a8e8510af81c2265078339146da26c02b8db39747c622
+size 108326

data/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0be20ce72ceb7fedb06196c8e44d55a6dced5e816da34d8171a5a3c926c74a7a
+size 5560076