Eckhard Bick - VISL

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capable - by “negative instantiation” 222 - of discarding all prototypes in the bundle. Prototype bundles are lumped together by CG set definitions, for instance: LIST = @%inst ; LIST = @%A @%AM @%AB @%zo @%D @%orn @%ent @%ich As can be seen, the prototype forms a bundle of its own , while the animal prototype bundle () consists of several sister prototypes. For the prototype bundle, the list of “killing features”, i.e. of features that - if discarded - disallows all prototypes in the bundle, is called in the set-definition section of the parsers semantic CG module: LIST = (@j @a @H @m @n @s @X @f @L @t) ; 223 Apart from the above mentioned H- and X- features (+HUM), the set includes - MOVABLE (j), -ANIMATE (a), -MASS (m), +LOCATION (L) and others. The actual prototype tag killing is performed by a simple CG rule: REMOVE (NOT 0 ) Note that the basic type of this rule has no context conditions, only tag or set membership conditions for the target itself. In practice, of course, a rule like the above could be split up into individual rules for every target prototype and atomic feature condition, and made more cautious or specific by adding real context conditions. Still, the basic idea of the rule is not to establish a context, but rather to implement a kind of feature inheritance reasoning, inferring one feature/tag from another: If a word form is not A, then it cannot be B either. One could also say that the rule helps to express (atomic) semantic feature information in terms of (complex) prototype bundles. Due to the way atomic features are lumped into prototype bundles, certain positive or negative atomic features imply certain others, and this, too, can be handled by rules expressing feature inheritance reasoning. Atomic features, like prototypes, have their own “killing sets”. In the prototype killing set only the essential, underivable, atomic features are listed for the prototype bundle concerned (here ), but information from other “secondary” features, is “translated” into disambiguation of primary features by feature inheritance rules: REMOVE (@=FEATURE) (0 @=feature) (NOT 0 ) ; REMOVE (@=feature) (0 @=FEATURE) (NOT 0 ) ; 222 i.e. by not being true in a given context with a given set of CG rules. 223 With the present CG-compilers, @-tags (i.e. tags to be disambiguated on the same tag line) cannot be AND-ed as is the case here. Rules involving contexts like must therefore be unfolded - at the latest, at compile time - into as many individual rules as there are AND-ed features in the set concerned. - 378 -
In the real rules, FEATURE is a positive atomic feature (capital letter), ‘feature’ a negative atomic feature (small letter). In the case of , the primary features j, H, s, L and t can draw on secondary features from outside the primary set. In the table below, all applicable “killing sets” for atomic semantic features are listed: - 379 -
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Eckhard Bick ♠ THE PARSING SYSTEM
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Abstract The dissertation describes
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3.7.2. Making the most of the lexic
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Inflexion tags 451 Syntactic tags 4
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first, - but soon, it would move th
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disambiguated), same level tags (to
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chain, but rather the linguistic co
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2 The lexicomorphological level: St
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The core of PALMORF is written in C
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(d) as part of words. For instance,
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(1) binary search technique: a . .
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acapitã#=#####B(orn)###413 acara#a
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Words with graphical accents often
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2.2.3.2 The inflexional endings lex
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2.2.3.3 The suffix lexicon (1) 1
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Suffix combination rules is also us
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an V a DERP a- [ANT] brad Vi as HV
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"inimigo" ADJ M P "inimigo" N M P
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variable word forms receive '_'- li
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The remaining 2 words of the 4-word
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appear truncated or not, depending
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comparison to the substring consist
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My present linguistic solution 28 i
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In some non-personal proper nouns,
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(i.e., not too complex) derivationa
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2.2.4.5 Abbreviations and sentence
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Another case, where meaning bearing
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2.2.4.6 The human factor: variation
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circumflex-) accented words without
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the tagger tries to identify a word
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xxxar-#1##AaiD######54578 endings-s
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"sombrancelha" N F P '=sobrancelha
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(6) Word class distribution and par
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VFIN 24.96 16 7.77 9 2.46 - - 25 3.
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the present participle by derivatio
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Inflexion tags combine with word cl
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2.2.5.2 The individual word classes
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SPEC "specifiers": independent pron
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WORD FORM and LEXEME CATEGORIES gen
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WORD FORM and LEXEME CATEGORIES dea
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mood VFIN finite IND indicative SUB
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prefixal derivation in verbs comple
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graph. def. characteristics: hyphen
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PP prepositional group de=aluguel
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2.2.5.3 Portuguese particles By ‘
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Deictic adverbs refer to discourse
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algo, algum=tanto, nada, nadinha?,
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quando når, da hvornår quanto [QU
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(1) Language distribution and error
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3 Morphosyntactic disambiguation: T
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(4) "quando" conjunction or adverb
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oth for the simple ambiguities intr
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case of a 3.person possessor, the u
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The fact that these semantic distin
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In (Karlsson et. al, 1995:19ff) an
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meaning- scope someone loves everyb
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• 5. Tags can be integrated as me
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19 0 0 - - - - >= 20 15 1 - - - - t
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Portuguese non-name words. Apart fr
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words: 40.8 10.5 17.9 2.9 0.5 3.1 8
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quite distinct, and few irregular e
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3.3 Borderline ambiguity: The limit
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(5b) They [saw(see) [the girl with
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Choose 'saw', if within the same cl
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ambiguous words), moving them to "l
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(3) modernização "modernizar" N
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3.5.1 Probabilistics: The 'fire a l
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In a brute force approach, for an a
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While undeniably involving more con
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Generative Grammar, introduced and
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node without branches matching the
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example is a grammar of one termina
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wide coverage tagging and parsing t
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ambiguity, Constraint Grammar can a
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syntactic reach of ordinary hand-cr
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“base form-1” .. .. WORD CLAS
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Base forms ("...") are tags like al
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play after base form rules targetin
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The above sequences are examples of
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3.7.2 Making the most of the lexico
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(1) number of CG rules containing a
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Intuitively, one might assume (a) t
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constructions. Something similar is
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are shaded, as well as the sum-colu
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For global context syntactic rules
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In table (4), three types of contex
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ules appear to be slightly more com
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(5a), continued ¡ ¢ number of con
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in the sequential “understanding
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all - 356 978 492 2219 C-percent 39
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3.8 Mapping: From word class to syn
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@ADVL [N-temp ADV PRP #ICL #FS #AS]
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@#AS-A< [ADV-rel] @#AS- @#AS-
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During the project period I have do
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syntactic errors around it, by prov
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1. Orthography and layout normalisa
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Of course, the use of dishesion mar
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S2 para aquele ... está perfeitame
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Parser performance on speech data (
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4 The syntactic level: A dependency
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subjects, but the second subject ca
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(7) SUBJ o [o] DET M S @>N 'the' b
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4.1.2 Dependency relation types: Cl
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(1) Table: Constituent structure ty
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Any further, more detailed, syntact
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discussion are inspired by Perini (
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Thus, we get ”Comeu peixe/bananas
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type-4 adverbials. Second, adverbia
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they all share one, and only one, c
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AB todos estes ambos os uns, uma,
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from personal pronouns, are not mut
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noun. Only very few adjectives (the
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4.2.2 The adpositional group head a
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However, adnominals can point to a
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(g) isso existe (até/nem (nos Esta
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4.3 The verb chain 4.3.1 The predic
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* aspect estar/andar/continuar/segu
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Ordinarily, 'o' is understood as su
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second verb's object 152 ), with so
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different subjects of matrix and su
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case function ± fronting ÷ fronti
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Quando ”quando” ADV @#FS-ADVL
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abalançar a kaste sig ud i at acab
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fazer xt, xd xdr få til at, lade s
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4.4 Clause types and clause functio
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@#ICL- non-finite subclause (combin
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While it is one of the clausality t
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(6) ..., tudo @S< pago @NN mão @
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(1g) Não [queria [comer outro bolo
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Apart from the presence of predicat
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demais [demais] DET M/F S/P @>N ‘
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element is a comparator and the sec
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without a predicator's valency info
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quantifying) cases, indicating adve
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4.5 Under the magnifying glass: Spe
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O assunto eram as ditaduras 2. F E
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The examples show that the normal "
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focusing function to the syntactic
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the quantifying adverbs mais and me
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qual DET @SC> @#FS-KOMP< antes era
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o [o] DET M S @AS< ‘that’ de [d
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[P=predicator, O=object, A=adverbia
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mais=de [mais=de] ADV @>A ‘more
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(2k) Ficou [ficar] V PS 3S IND V
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interno [interno] ADJ M S @N< '-'
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a preposition, por, then allowing f
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4.5.3 Tagging the quantifier 'todo'
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connection with personal pronouns -
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4.5.4 Adverbial function 4.5.4.1 Ar
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explanation for this may be that a
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a [a] DET F S @>N ‘the’ pergun
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carro [carro] N M S @SUBJ> ‘car
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pass the second test ('*De seu novo
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Therefore, the @ADV-@ADVL distincti
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@PIV, @ADV and @SC are - unlike @AD
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heads a "material" PP. The followin
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4.5.4.3 Intensifier adverbs Intensi
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4.5.4.4 Complementiser adverbs: Int
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complementiser in nominal FS or ICL
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hooked AS-relatives (3) they even a
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4.5.4.5 Adverb disambiguation and o
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position: adverb class: A) set oper
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(5b) fits fairly well into the (A)
Page 328 and 329: antes/depois+de Depois [depois] AD
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Page 332 and 333: In (4d) ter ('have') does have mono
Page 334 and 335: When the potential subject is post-
Page 336 and 337: (1) Table: functions of pronominal
Page 338 and 339: ditador [ditador] N M S @N ‘-’
Page 340 and 341: In other contexts, para is not usua
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Page 344 and 345: SPEC DET/SPEC ¬ @#FS/AS-N< artic
Page 346 and 347: 4.6.3 Tree structures for constitue
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Page 352 and 353: 4.7 Elegant underspecification An i
Page 354 and 355: 5 The uses of valency: A bridge fro
Page 356 and 357: Returning to a research view concer
Page 358 and 359: 5.2 Valency instantiation: From sec
Page 360 and 361: Note that valency is treated as a f
Page 362 and 363: REMOVE (@%vt) (0 @%vK) (*1C @
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Page 366 and 367: than by asking ‘is it an A?’ or
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Page 372 and 373: In all, the parser uses 16 atomic s
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Page 376 and 377: 6.5 A semantic Constraint Grammar I
Page 380 and 381: LIST = (@=c @=v @=p @=s @=t) ; LIS
Page 382 and 383: um verão ‘a summer’ * ok. * f
Page 384 and 385: An example of argument-head polysem
Page 386 and 387: The program module implementing the
Page 388 and 389: REMOVE (@=X) (*1 @%jn BARRIER @NON-
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Page 392 and 393: Note that the MT engine will choose
Page 394 and 395: Even where none of the semantic rul
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Page 398 and 399: O Itamarati +HUM @SUBJ The Itamara
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Page 404 and 405: descriptional complexity: 'full tag
Page 406 and 407: Here, each line of the CG-notation
Page 408 and 409: 7.2 Grammar teaching on the Interne
Page 410 and 411: system's disposal. After acquiring
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Page 418 and 419: The tree structure of the sample se
Page 420 and 421: (5) Syntactic tree structures (VISL
Page 422 and 423: two function tags, since the studen
Page 424 and 425: 7.3 Corpus research In the case of
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- 428 -
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The NURC speech corpus (“Norma ur
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7.4 Machine translation 7.4.1. A te
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processors used by translators or l
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The following diagram shows how dif
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8 Conclusion: The advantages of inc
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- 440 -
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Sources: English: EngCG: Karlsson e
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(4) Table: syntactic tree structure
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lexicon which ensure removal of fal
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8.2 CG Progressive Level Parsing: G
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Methodologically, it is commonly cl
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$ the dollar sign is used to mark n
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@#ICL-AUX< argument verb in verb ch
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"unit" noun (e.g. "20 metros") att
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SEMANTIC TAGS The tables below prov
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ANIMATE NON-HUMAN, NON-MOVING bo 13
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stof 136 fabric seda ‘silke’ ma
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(-CONCRETE, - MASS, +COUNT) ‘modu
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ax 25 plus below: (-CONCRETE, -MASS
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cI 199 process (-CONTROL, imperfect
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oot search lexicon search takes a w
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translation, prepares bilingual lex
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in a typical van/von-name chain con
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Appendix: Example sentences The fol
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é [ser] V PR 3S IND VFIN @FMV quas
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será [ser] V FUT 3S IND VFIN @FMV
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julgamento [julgamento] N M S @P< $
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Os [o] DET M P @>N sabonetes [sabo
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parte [parte] N F S @P< de [de] PR
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inesquecíveis [inesquecível] ADJ
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Literature Almeida, Napoleão Mende
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Lindberg, Nikolaj, “Learning Cons
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Alphabetical index Page numbers in
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averbal subclauses;254 finite subcl
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attributive;249 nominal;248 finite
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for auxiliary definition;235;237 pa
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subject identity test;236 subjects
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ERROR: rangecheck OFFENDING COMMAND
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