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translation-meta-codecs

The groupant beside models/translation-meta-codecs.groupant in the Mova repository: what the code computes, what it never does, how to go back from its outputs, its invariants, cost and checks.

Facts

Implementation material. A Mova code model describes this code at one source revision: partial models, finite checks and their stated scope. It is not a reviewed general exposition, and its labels are shown as written, never raised.

Components

componentlabelwhere
approximantpartialforward
astnot materialized
compositionpartialcomposition
costsymbolic source derivedcost
descriptantpresentdescriptant
invariantpartialinvariant
testssee source local evidencechecks

Obernants

The typed relations around the forward model: the behaviour complement (what the code never does), the reverse reconstruction (every input compatible with an output) and specialised views.

idtypelabelwhere
behavior-complementbehavior_complementpartial source derived modelbehavior-complement
reverse-reconstructionreverse_reconstructionpartial source derived modelreverse-reconstruction
owner-signaturerepresentation_transportpartial source derived modelowner-signature
head-coordinatecoordinate_transportpartial source derived modelhead-coordinate
logical-gatelogical_multiset_gatepartial source derived modellogical-gate
normal-versus-residualresidual_conditioned_identitypartial source derived modelnormal-versus-residual

Model text

descriptant

translation-meta-codecs: wave32

Hebrew Reader train owns meta tokens through IBM then Strong override; owners feed HebEncoder train. meta MTok ctx_keys feed profile and HebEncoder; Fw/Rule remap their heads. Logic consumes event concepts via Lexicon and LCS. Strong is optional alignment input, not a translation oracle.

This source-bound partial group organizes existing Mova code. Native evidence and excluded effects are recorded in source sidecars and the root wave32 report. Registration is not a universal proof or whole-system runtime claim.

model

translation-meta-codecs

forward

Meta tokens and lexicon provide shared representation; profile and Hebrew encoder choose context chunks, IBM+Strong supply Hebrew ownership, Fw/Join/Reorder and Rule transform tokens, Logic compares mapped event facts. These are tagged paths, not one mandatory chain.

invariant

Valid 1-based heads/root0 and finite representable counters; metadata projection and retained residuals remain explicit. Deterministic ordered maps and strict comparisons fix ties on admitted finite domains.

cost

LCS O(nm); IBM Isum target(source+1)*log(row) plus rows; token transforms up to quadratic/cubic head and subtree scans; four-level context maps include key bytes. Real pipeline cost is sum along selected path, not all sibling helpers.

composition

Hebrew Reader train owns meta tokens through IBM then Strong override; owners feed HebEncoder train. meta MTok ctx_keys feed profile and HebEncoder; Fw/Rule remap their heads. Logic consumes event concepts via Lexicon and LCS. Strong is optional alignment input, not a translation oracle.

domain

Small synthetic tokens, initialized tables, finite nonnegative weights, valid coordinates; Rule Drop acyclic; LCS <=65535 and counts/arithmetic representable.

limitations

Real annotator/morph loading, corpus filesystem parsing, full training/evaluation and teacher paths remain unexecuted. Residual exactness is diagnostic reconstruction, not semantic understanding.

checks

catalog

behavior-complement

Valid head-remapping transforms do not retain deleted coordinates; exact residual gates do not entail exact normal translation. Logical-word equality does not imply equal propositions.

reverse-reconstruction

Compatible antecedents include lost surface spellings, metadata/switches, dropped tokens and hidden owner assignments; uniqueness requires full stored scripts and source-side parameters.

owner-signature

Reader owners map each meta token to optional Hebrew index; HebEncoder emits only first encounter per owner, losing later assignments.

head-coordinate

MTok uses1-based heads/root0; each structural transform must renumber positions after dropping/reordering, while span retains source coordinates.

logical-gate

Delta gate compares sorted logical_words of bare concept and chunk, preserving duplicates and normalizing selected numerals. Event comparison is separate: permutations preserve verb-multiset gaps, while LCS pairing (including repeated-verb ties) can change contradictions and distance.

normal-versus-residual

Hebrew measure computes ordinary text exact/chrf before diagnostic target residual reconstruction; gate_ok can hold for empty learned encoder.

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