Cianmcnally/verbweave-opus-mt-en-de

verbweave — English→"Denglish" verb placement (opus-mt-en-de fine-tune)

Takes an English sentence and produces the same sentence with only the main verb translated to German, positioned where German grammar puts it:

She has eaten the apple already.   ->  She has the apple already gegessen.
I get up early on weekdays.        ->  I stehe early on weekdays auf.
Do you drink coffee?               ->  Trinkst you coffee?

This is not translation — it is a constrained edit for diglot-weave language learning, where readers acquire vocabulary and word order from context while still reading their own language.

Model

Fine-tuned Helsinki-NLP/opus-mt-en-de (MarianMT, 74M params), weight-averaged across the best runs ("soup"), exported to int8 ONNX for in-browser use with transformers.js. ~25ms/sentence with beam 4 on CPU.

Evaluation

1,421-row held-out set, all 20 German word-order constructions, leak-checked (0.1% near-duplicate contamination). "Honest" = the German verb is semantically right (valid synonyms allowed) and correctly placed.

architecture	size	exact	honest
dictionary substitution (baseline)	—	21.9%	—
one-shot gemma-3-270m	270M	65.4%	73.8%
this model	74M	67.3%	75.4%
one-shot EuroLLM-1.7B	1.7B	71.3%	79.3%

The dictionary baseline scores 0% on every construction where the verb moves — it cannot move a word. A 6×-bigger German-specialised LLM gains only 4 points of "honest" over this model at 20× the size.

Training data

32,159 examples generated with Claude across a 20-construction × 39-verb-group grid, every row structurally validated (only the verb may change; multiset comparison of the non-verb tokens). Published separately as the verbweave dataset. Training data is LLM-generated, so LLM German is the accuracy ceiling.

Limitations

• Separable and reflexive verbs are the hard cases (both halves of stehe … auf must be recalled).
• Informal du register from the training data occasionally disagrees with MT's formal Sie.
• English input only; sentence-level (no document context).