PaNoLa: Parsing Nordic Languages
Eckhard Bickhttp://beta.visl.sdu.dk
PaNoLa Goals
● 1. Integrate existing and stimulate new Constraint Grammar-research in Nordic countries
● 2. Internet based Grammar Teaching, applying theVISL model to different Nordic languages
● 3. Morphologically and syntactically annotated corpus data
Participants● University of Southern Denmark (Eckhard Bick, Anette Wulff)
Danish CG as well as CGs for 6 other languages
● Oslo University (Janne Bondi Johannessen, Kristin Hagen)Bokmål and Nynorsk CGs
● Helsinki University (Fred Karlsson):Finnish and Swedish CGs
● Göteborg University (Torbjörn Lager)µTBL-system (corpus trained automatic CG)
● Tartu University (Heli Uibo, Kaili Müürisep): Estonian CG
● Tromsø University (Trond Trosterud): Sami CG
● The Greenlandic Language Secretariat Oqaasileriffik (Per Langgård)
● Iceland University of Education (Jóhanna Karlsdottir)
● University of the Faroe Islands (Zakaris Hansen)
Project framework
● Funding: Nordic Council of Ministries● Funded project period:
PaNoLa: January 2002 – December 2003: da, no, sv, fiPaNoLa-addon: 2004: is, fo, smi, kl
PaNoLa-plus: 2005 (- 2006): is, fo, smi, kl planned: PaNoLa-neighbour: 2005/6 (- 2007): lit, lav, ru
● Historical basis and ongoing cooperation
PaNoLa PaNoLaaddon PaNoLa-plus
PaNoLa-neighbour
da, no, sv, fiis, fo, smi, kl
lit, lav, ru
Project framework
● Network aspect: 4 workshops in Denmark, Norway, Iceland and Sweden
Odense, 19.-21. May 2002 Ustaoset, 25.-27. October 2002 Reykjavik, 1.-2. June 2003 Göteborg, 24.-25. October 2003Odense, 23.-26. October 2004Fefor, 11.-13. Marts 2005(Tallin, 1.-3. April 2005)planned: Thorshavn, 16.-19. September 2005
● Administration, Web-server, Data-integration:VISL/ISK, University of Southern Denmark
● Satellite projects: e.g. Arboretum, GREI, Arborest
Constraint Grammar
● Rule and lexicon based robust parsing (Karlsson et. al. 1995), methodological paradigm
● Shared conceptual and notational conventions, allowing productive research transfer
● Language dependent differences: Lexicon, rules(Inter-scandinavian comparative payoff?)
● Compiler and rule type differences● Focus differences: tagging? Parsing? Semantics?
Teaching? Corpus annotation? QA?, NER?, ...
Rule formalism and architecture
cg1-compiler cg2-compiler
visl-cg-compiler
SweCG
FinCG
Oslo-Bergen tagger
DanGram, Samiother VISL languages
µ-TBL
Lingsoft-compatibleNeeds more rules than cg2
Sets as targetsBarrier-
conditions
“cg2-like” plus substitute operator
for correcting hybrid input
Automatic learning,
local context,rule ordering
PoS
Syntax
Case roles
Swedish orlanguage-indep.trained CG
☻cgx-compiler
EstCG
da
smino
estsv fi
The Lexical Base
TWOL Core lexicon +morphological analyser
SweCG
FinCG
Oslo-Bergen tagger
DanGram
Corpusdependent
Valency potential (especially for verbs)
Semantic setsNER
µ-TBL
Full semantic prototypelexicon
SamicCG
EstCG
Theoretical Framework (Syntax)
Cg2tree (MC)(visl-psg)
Traditional CG: Flat dependencyWord based form and function tags
Dependencyfilter (SH)
TIGER formatPENN format
Visl2penn(EB)
Visl2tiger(LN, EB, ..)
Treebank format
PSG-Grammar
DanishNorwegian
Editing tools
Search interfaces
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Korpus90/2000Oslo-Bergen Corpus
Arboretum
Redwood
Treebank data compatibility
CG CG-dep VISLVISL-dep
TIGER TIGER-dep MALT-depDTAG-dep
CGcg2depdepsplicator
cg2visl(visl-psg + grammar)
depsplicator
cg2visl | visl2tiger.pl
cg2visl | visl2tiger.pl | tiger2dep.pl
cg2dep | visldep2malt
depsplicator
CG-dep
visldep2malt
VISLtree2cg
visl2tiger.plvisl2tiger.pl | tiger2dep.pl
visl2tiger.pl | tiger2dep.pl | tigerdep2malt
VISL-dep
TIGER tiger2dep.pl
TIGER-dep
tigerdep2malt, (NTN tools)
(NTN tools)
MALT (NTN tools)
DTAG (NTN tools)
Accessibility
● Strong focus on making tools and corpora freely accessible on the internet
● Provide notational and complexity filters to bridge differences between different research and teaching traditions
● VISL's open source philosophy for reconciling academic and commercial use:Free compilers and corpora, but allowing for the protection (i.e. commercializability) of grammars, lexica and end-user applications
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Related applicative CG-projects
● CG spell/grammar checking (No, Da)Lingsoft / Microsoft
● Named Entity Recognition (Da, No)Nomen Nescio (Nordic Network) 2001-2003
● Treebanks (Da Arboretum, Norwegian plans) Nordic Treebank Network 2003-2004
● Question Answering systems (Da)Aminova Dialogue Systems
● Teaching (e.g. VISL-GYM, VISL-HHX, GREI)
PaNoLa's other leg: CALLIntegrating and strengthening Nordic languages
in the VISL grammar teaching system
● A unified system of grammatical categories and structural analysis for 22 languages (Dienhart 2000 and Bick 2001)
● Color codes and symbolic notation● Systematic focus on form & function● Preexisting server and programming infrastructure● School and university teaching contacts at all levels● Internet based games and exercises● Graded complexity filters
notational harmonization vs. linguistic differences:The greenlandic example
QUE:parCJT:cl=S:pron Suumuna #'Hvilken/Hvad'=fA:icl==Od:g===D:n naasut #'planternes'===H:n qorsuttaat #'deres det grønne'==P:v-pcp1 kiilorpassuakkaarlugu
#gørende det i kilovis=A:g==H:n nunamut #'jorden'==D:n uumassuseqanngitsumut
#'på den livløse'=P:v siaruartilertaraa
#får det til at brede sigCJT:cl-=fA:cl-==S:n apullu #og sneenCO:conj _lu-CJT:cl=-fA:cl==P:v aanniariaraangat
#så ofte den begynder at smelte=P:v siaruaatipallatsittarlugu
#får det til at vælte frem?
KAL22a)Suumuna naasut qorsuttaat kiilorpassuakkaarlugu nunamut uumassuseqanngitsumut siaruartilertaraa apullu aanniariaraangat siaruaatipallatsittarlugu? (Hvad var det der gjorde, at kilo efter kilo af det grønne plantestof kunne vælte frem fra den livløse jord, lige så snart det blev varmt nok i vejret og de sidste rester af sne var væk?)
==H:n nunamut #på jorden===R:n('nuna') nuna-===D:in('mut',fleksiver) -mut
==D:n uumassuseqanngitsumut===R:v('uuma') uuma-===D:in('ssusiq')-ssuse-===D:iv('qar') -qa-===D:iv('ngngit')-nngit-===D:in('Tuq') -su-===D:in('mut',fleksiver) -mut
==P:v aanniariaraangat===R:v('aak') aan-===D:iv('niar') -nia-===D:iv('riar') -riar-===D:iv('gaangat',fleksiver) -aangat
=P:v siaruaatipallatsittarlugu==R:v('siaruar') siarua-==D:iv('ute') -ati-==D:iv('pallak') -pallat-==D:iv('tit') -sit-==D:iv('Tar') -tar-==D:iv('lugu',fleksiver) -lugu
Greenlandic word-internal tree structures
Teaching corpora
Se nte nce s W o rd s W o rd s p r.se n te nce
D a n ish 11 2 1 + 1 2 0 2 9 1 0 ,1
B o k m å l 7 6 6 5 6 2 9 7 ,3
N y n o rsk 7 6 6 5 8 8 8 7 ,7
Ic e la n d ic 2 1 2 1 3 9 4 6 ,6
F a ro e se 1 7 8 1 6 0 9 9 ,0
Sa m i 1 5 5 + 6 0 3 3 ,9
Sw e d ish 1 0 6 11 5 3 1 0 ,9
F in n ish 1 0 2 5 4 5 5 ,3
E sto n ia n 1 0 0 + 5 9 6 6 ,0
G re e n la n d ic 1 0 0 ? ? ?
● Pedagogically structured● XML-markup for teaching topic and didactical progression● Finnish and Swedish modelled on Danish and Norwegian examples files (comparative possibilities)● compatibility with and importability for research treebanks (e.g. Sofie)
Interactive teaching trees
Grammar games: Labyrinth
Grammar Games: Word Fall
Integrating the CG and CALL legs
● Nordic CG expertise is used to provide live analyses as input for the teaching modules, if necessary by CGI-communication between university servers, e.g. Oslo-SDU
● Descriptional harmonization issues (e.g. Word class)● Determine matching complexity (e.g. subclause analysis?)
CG leg evaluation
● CG-grammars improve incrementally, so evaluation is less definite than for probabilistic systems, and can change over time.
● Results depend on tag granularity and test genre
● Some numbers:-- DanGram: F-Score 98.65 for PoS, 94.9 for function (Bick 2003)-- DanGram NER: 5% typing errors, 2% chunking errors-- Bokmål CG: 97.2% lexical F-score (Hagen & Johannessen 2003)-- Nynorsk CG: 96.2% lexical F-score-- SWECG 1.0: recall 99.7% at a precision of 95% (pre-PaNoLa)-- µ-TBL CG for Swedish: 98.1% lexical accuracy when allowing for 1.04 tags pr. Word (Lager 1999)
Teaching leg evaluation● GREI evaluation: improvement of grammatical skills
after using VISL tools (104 children 7th and 8th grade)● Same level tests before & after using VISL/GREI, test &
control groups● Subjective results: All users thought VISL was more fun
(games more than trees), and that their grammatical skills had improved
● Objective results: Test group performed 14.5% better than control group (7th grade), resp. 7% (8th grade) and 12% at the secondary level.
● Differences were positive for both PoS and sentence analysis, but more marked for the latter
Teaching corpora differences across PaNoLa languages
● Preposition frequency: 11% (Bokmål), 11.4% (Danish), 13.4% (Nynorsk), 0.5% (Finnish)
● PoS: “klappe i”, “tage på”, “skrive noget om”are tagged as ADV in Danish, as PRP in Norwegian samples
● Danish infinitive markers ('at') tagged as CONJ in Norwegian● Subclass solutions: e.g. Da/Fi distinction between adjunct and
argument adverbials, not made by No/Se (fA/As/Ao vs. A)● Tradition interference: Swedish analysis had zero
constituents, because it was annotated according to the English VISL model
Outlook● Continued development of Nordic Constraint
Grammars and CG applications● Ongoing CALL service for schools● Presence of the CG paradigm in other Nordic networks● “Post-PaNoLa”: VISL adaptations for other minor
Nordic languages (Faeroese, Icelandic, Samic, Estonian ...)