In class yesterday we annotated an L2 Russian narrative for case and aspect and then ran it through DeepL via Trados Studio 2022. The output flattened aspect and drifted on agreement — does any workflow or plugin let you pass POS/morph tags or lock function words so the engine honors those grammatical cues, or is this strictly custom MT territory?
You can’t pass POS/aspect to DeepL through Studio — that’s custom MT — but you can get close by ‘locking function words’ via a custom file type (Regex > treat as protected content; think traffic cones for your prepositions) and forcing key lemmas with the DeepL glossary in the plugin (Introduction - DeepL Documentation). Small caveat: over-protecting tanks fluency and tag projection. Which aspect pairs are breaking most for you?
I’ve had better luck in Studio 2022 by pre-tagging verbs with lightweight markers like [PFV]/[IPFV] via a custom XML filetype so they show as inline tags; DeepL usually carries the cue through, and I strip them after with SDLXLIFF Toolkit (https://appstore.rws.com). It’s a bit brittle, but on L2 Russian narratives it cut the aspect flattening and agreement drift — would you be open to trying that, or do you need a pure plug‑and‑play setup?
One workaround: do a pre-pass that wraps aspect-marked verbs and any must-keep particles in harmless tags, push it through Microsoft Translator via the MT Enhanced Provider (tends to honor tags better than DeepL’s Studio connector), then strip on return — training wheels, but effective. @sophia_m92, your “[PFV]/[IPFV]” markers map cleanly to …; if you want, I can share a tiny Regex pre/post script, and here’s the plugin: https://github.com/RWS/MT-Enhanced-Plugin.