1. Constraint Grammar ESSLLI
Friday:
What you can do with Constraint Grammar

2. CG Input remember CG is modular!
output from one module becomes input to the next module
pre-
processor
analyzer
nomorph CG
your CG
text
output
cat file | preprocessor | analyzer | vislcg3 -g engcg.nomorph.cg | vislcg3 -g yourcgfile ...
echo ”text” | preprocessor | analyzer | vislcg3 -g engcg.nomorph.cg | vislcg3 -g yourcgfile ...

3. CG Applications Corpus enrichment
adding ”searchables”, i.e. markup of implicit information for explicit searches
definite/indefinite noun phrases
complex tenses, aspect
secondary nexus relations
###### definite np ###
LIST DEF-EDGE =
"the" ("each" DET) ("every" DET) ("all" DET) GEN <poss> (<dem> DET) NUM ; #
SUBSTITUTE (N) (<def> N) TARGET (N NOM)
(*-1 DEF-EDGE BARRIER NON-PRE-N/ADV) ;
SUBSTITUTE (N) (<def> N) TARGET (N NOM) (c DEF-EDGE) ;
###### complex tense ###
SUBSTITUTE (V) (<fut> V) TARGET
(p VV LINK 0 ("will") OR ("shall")) ;

4. CG Applications Text markup for Information Extraction / Retrieval
Named Entity Recognition (NER) for news feed filtering
Time & Place contextualisation of events
Sentiment marking
Sect members won political control of the nearby community of Antelope, renaming it City of Rajneesh, and attempted to control voting in Wasco County by busing thousands of homeless people to the commune in 1984.
ADD (%LOC) TARGET
(*-1 PRP LINK 0 ("in") LINK 0 OR ; # Place: in
ADD (%LOC-TMP) TARGET
(-1 ("in" PRP)) ; # time: in 1998

5. CG Applications Anaphora / referent resolution
pronoun resolution for Machine Translation (MT)
reflexive vs. non-reflexive
NP anaphora:
synonyms, variation (matching of semantic class)
syntactic links: @FS- N<
The Mediterraneans occupy the center of the stage. Alexander Militarev suggests that their homeland was in the Levant. Specifically, he identifies them with the Natufian culture.
SETRELATION (ref) TARGET ("he")
(0 (NOM) OR (ACC))
TO (**-1WA + N-HUM
LINK 0 (S) LINK NOT 0 <fem>
LINK NEGATE
BARRIER VFIN OR ;

6. CG Applications
Grammar checking (ORDRET: Danish, LingvoHelpilo: Esperanto)
better ordering of spelling correction alternatives, using contextual tests
can be done by running an existing CG disambiguator grammar on the output of a spellchecker
mapping of grammatical error types
agreement errors, even long-distance (subject complements, relative clauses
verb chain inflexion erros
reordering of constituents (untried!)
rules can be named --> pedagogical comments on error types
I think he definitely prefer another day.
ADD (§3S) TARGET (V -3S) OR (INF) OR (IMP)
(*-1C (S NOM) OR (3S NOM)
BARRIER NON-ADV
LINK *-1 VV OR CLB OR >>>
BARRIER (KC)
LINK NOT 0 (<xt>)) ;

7. CG Applications Machine Translation (MT)
Indirect: e.g. add person / number on English verbs for translations into Romance og Slavic language
They shared a common vision.
The board member shared a common vision.
He and Peter shared a common vision.
LIST PN = 1S 2S 3S 1P 2P 3P ;
SUBSTITUTE (-3S) $$PN TARGET VFIN
(c LINK cS $$PN) ; # unification generalisation
SUBSTITUTE (IMPF) (IMPF) + $$PN TARGET VFIN
(c LINK cS $$PN) ; # unificationgeneralisation

8. CG Applications Machine Translation (MT) Direct mapping translations
handling polysemy or usage distinctions
The new board members shared a common vision - promising that share holders would get their share of the year's earnings
ADD (§DE-TRANSLATION:Aktien-)
TARGET ("share" N ; # share holder, share price
or with dep-relations:
ADD (§TRANSLATION:Aktien-)
TARGET ("share" N NOM) (p N) ;
ADD (§DE-TRANSLATION:Anteil)
TARGET ("share" N S) (-1 (<poss>)) ; # get one's share

9. CG Applications Machine Translation (MT)
Reordering: moving dependency tree sections
SVO --> SOV
ADJ N --> N ADJ
SUB, S, ADV, V -> SUB, S, V, ADV
The new board members shared a common vision
MOVE WITHCHILD (*) TARGET BEFORE NOCHILD (p &MV) ;
The new board members a common vision shared