Difference between revisions of "Recursive transfer"

Revision as of 09:23, 8 October 2014

~~Make the parser output optionally original parse tree (SL syntax) and target parse tree (TL syntax).~~
Attribute structures. These are defined in typical .t1x format with def-attrs
Make the parser robust — we should never get parse errors, though our trees may be mangled.

The parser has two trees, both are built simultaneously:

When a sentence terminal (S) is reached, the target tree is traversed and printed out.

What to do with a parse-fail.
- Implicit glue rules
  - How do we make sure that we never get Syntax error (e.g. really robust glue rules).
- the glue rules would not compute anything, just allow for partial parses
How about unknown words...
- they would be some non-terminal UNK that would be glued by the all-encompassing glue rule from above.
Ambiguous grammars -> can be automatically disambiguated ?
- Learn shift/reduce using target-language information ?
Converting right-recursive to left-recursive grammars.
How to apply macros in rules which have >1 non-terminal.
What on earth to do with blanks / formatting...
Do we try and find syntactic relations in the transfer, or do we pre-annotate (e.g. with CG) then use the tags from CG to constraint the parser?
Can/should we do unification in the grammar (e.g. to avoid rules like SN -> adj n matching when adj.G and n.G are not the same)?
If a language uses CG, the rule SN -> @A→ @N would only match where CG mapped @A→ (and CG can do unification with less trouble, not mapping @A→ where gender differs)
- However, if we are to propagate attributes up the tree as well, it makes sense to have unification as well, so we can say NP[gen=X] -> D[gen=X] N[gen=X]
Should the transfer allow for >1 possible TL translation ? to allow 'lexical selection' inside transfer as well as outside ?
Can we learn transfer grammars from aligned treebanks ?

Prószéky & Tihanyi (2002) "MetaMorpho: A Pattern-Based Machine Translation System"
White (1985) "Characteristics of the METAL machine translation system at Production Stage" (§6)
Slocum (1982) "The LRC Machine translation system: An application of State-of-the-Art ..." (p.18)

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 [[Category:Development]]
 [[Category:Transfer]]
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