Datasets:
Competitive position — where we stand vs Google / DeepL / NLLB
Honest snapshot (2026-07-21).
Law: (S=K(T_1+T_2+T_3)) pin D1D38A (FSOT; competitors have no equivalent).
Two different games
| Game | What “accuracy” means | Who owns the public narrative |
|---|---|---|
| A. Form→gloss inventory | Word/lemma → meaning under densify | PFLT is very strong |
| B. Sentence fluency (MT) | Full sentence → fluent EN (BLEU/chrF/COMET) | Google / DeepL / NLLB |
We are competitive / leading on A.
We are climbing toward B, not at parity yet.
Our numbers (measured in-repo)
A — Form→gloss solidify (catalog)
| Metric | PFLT |
|---|---|
| Languages | 113 |
| OPEN / PRODUCT form→gloss | ~99.99% |
| Thin langs (n<50) | 0 |
| Breadth vs Google ~249 | ~45% of lang count |
| Breadth vs NLLB ~200 | ~56% |
| vs DeepL ~30–100 langs | At/above DeepL scale on count |
This bar is not what Google advertises — but it is real offline inventory depth (incl. classical/historical).
B — Sentence fluency (dual student: densify + neural)
B1 — Chat/Tatoeba domain (16 langs; latest SOTA push 2026-07-21):
| Path | Metric | PFLT | Note |
|---|---|---|---|
| Product densify + residual TM | BLEU-4 / B1 / U-F1 | ~83 / ~98 / ~92 | Product ceiling (includes chat residual templates) |
| Neural open-set (best of opus/NLLB/mul per lang, ≤200/lang) | mean sacreBLEU | ~50.2 | Fair chat bar — past staged 45 |
| Hybrid oracle densify|neural | mean sacreBLEU | ~53.6 | Upper bound for router |
Per-lang neural peaks: it 68, es/pt ~61, de/ru ~57–58; thin: hi ~55; CJK gap: ja ~37, zh ~32; classical la densify still wins (48 product).
B2 — News domain (public WMT14 de→en test, n=3003) — harder bar:
| Metric | PFLT densify-only | PFLT neural student (local) | DeepL-class band |
|---|---|---|---|
| sacreBLEU | ~0.4 | ~33.9 (opus-mt-de-en beams=5; NLLB-600M ~33.4) | Often ~40–48+ |
| chrF | low | ~60 | Higher |
| Gap to staged mid bar (40) | — | ~6.1 | — |
| Gap to stretch (48) | — | ~14.1 | — |
Domain split: chat neural is past mid bar (~50 mean sacre); news still ~6 BLEU short of DeepL-class mid. Densify alone does not transfer to news — hybrid router is the product path.
*Literature ranges, not same-day FLORES A/B. FLORES data files still 403 (README ok; parquet gated — re-check Hub “Access granted”).
Law / uniqueness (no competitor equivalent)
| Metric | PFLT |
|---|---|
| Live pin D1D38A | Yes |
| Offline classical + visual path | Yes |
| Densify without rewriting law | Yes |
Are we competitive at all?
| Track | Competitive? | One-line |
|---|---|---|
| Offline form→gloss multi-lang | Yes — strong | Near-ceiling on our catalog |
| Catalog breadth | Mid | 113 of ~200–249; beating DeepL count band |
| Classical / dead / hieroglyph | Yes — unique | Weak/absent in consumer MT |
| Chat sentence (neural open-set) | Yes — mid/high open MT | Mean sacre ~50 (Tatoeba-style) |
| News sentence (WMT de-en) | Near mid open MT | ~34 sacre; ~6 to DeepL mid bar |
| Top DeepL commercial SOTA | Not claimed | Need +6 to +14 sacre on news |
| Cloud UX / latency | N/A | Different product (local Ada) |
| FSOT law grounding | Category of one | — |
Short answer:
Yes on inventory, classical, offline FSOT, and chat neural open-set.
Almost mid-parity on news WMT (34 vs ~40 staged); not full DeepL stretch (48).
Hybrid densify|neural is the product route (oracle mean chat sacre ~54).
How far to go (gap to “parity”)
Define stages (honest):
| Stage | Domain bar | Where we are |
|---|---|---|
| S0 Dict word map | <5 BLEU | Passed |
| S1 Phrase densify | ~10–20 | Passed |
| S2 Strong chat content | ~25–35 BLEU | Passed (neural chat mean sacre ~50) |
| S3 Mid neural news / good EU | ~35–45 sacre WMT | ~34 HERE — gap ~6 to 40 |
| S4 Strong neural / DeepL-class | ~45–55+ sacre | Gap ~14 to 48 stretch |
What must rise for S3–S4
| Lever | Why | Status |
|---|---|---|
| Hybrid router densify|neural | Product best-of path | Oracle measured (~54 chat mean); ship in Ada |
| Word order / T3 (esp. ja/zh) | BP kills densify BLEU despite B1 | Route CJK to neural (ja/zh already) |
| FLORES / WMT same-file eval | Comparable claim | FLORES data still gated; WMT14 scored |
| Neural student (NLLB/opus-mt) | Fluency generators | Done multi-system; optional 1.3B / finetune |
| Domain match (news vs chat) | DeepL trains news/web | Need more WMT densify or student finetune |
FLORES status
- Account can read README of
facebook/flores. - Data parquet still returns 403 (gated) — accept may be pending, wrong dataset page, or needs re-login/approval.
- Action: open https://huggingface.co/datasets/facebook/flores while logged in → confirm Access granted (not just license text).
- Until then we report Tatoeba product densify + WMT as public bars, not FLORES.
Bottom line
| Question | Answer |
|---|---|
| Competitive on form→gloss / offline catalog? | Yes |
| Competitive on chat open-set neural? | Yes — mid/high open MT (~50 mean sacre) |
| Competitive on Google/DeepL news fluency? | Not parity; S3 (~34 WMT sacre; ~6 to mid bar) |
| How far on news sacreBLEU? | ~6 pts to staged 40; ~14 pts to stretch 48 |
| Unique advantage? | FSOT law + classical + offline densify + hybrid student path |
Public storefront: HF dappalumbo91/pflt-fsot · Kaggle damianpalumbo/pflt-fsot-benchmarks · GitHub tag/docs RELEASE_v0.2.0.
We do not claim DeepL parity. We do claim a real, measured climb under fixed FSOT law, with high content-level scores and mid full-sentence BLEU.