Eckhard Bick - VISL

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The overall frequency of unanalysable words, however, is quite stable: For both the literature and the Borba-Ramsey corpora, as well as for VEJA news magazine texts, the figure is roughly 0.4%. - 98 -
3 Morphosyntactic disambiguation: The holographic picture 3.1 The problem of ambiguity: A pragmatic approach 3.1.1 Relevant ambiguity Handling and resolving ambiguity is the central mechanism in the Constraint Grammar formalism. So, in a way, it seems reasonable to assume that which types of ambiguity are specified will condition the kind (and quality) of the grammatical description to be achieved. In a modular, level based, parsing approach, it makes sense to classify ambiguities according to the morphological, syntactic, semantic (and possibly, pragmatic) levels, and then to address the problem of ambiguity with similar tools at ever higher levels, while exploiting different levels and increasing amounts of lexical and contextual information. In this process, any advance in disambiguation on one level would improve the informational leverage for the next level. In this vein of layered analyses, homonymy can be defined as morphological ambiguity, involving (1) free morphemes (lexical ambiguity), (2) bound morphemes (inflexional ambiguity), or (3) both (lexico-inflexional ambiguity). (1a) lexical (base) (free morphemes) different base forms, same categories - foi "ir" V PS 3S ('he went') -foi "ser" V PS 3S ('he was') (1b) lexical (PoS) same base form, difference in category inventory and -type - complementar V ('to flatter') - complementar ADJ ('complementary') (1c) lexical (paradigm) same base form, difference in one or more lexeme categories - guarda F' ('guard' [group]) - guarda M' Morphological ambiguity (homonymy) - 99 - (2) inflexional (bound morphemes) same base form, difference in one or more word form categories - amamos PR 1P - amamos PS 1P (3) lexico-inflexional (free/bound morphemes) different base forms, difference in lexeme- AND word form categories - busca N F S ('search') - busca V PR 3S ('he searches')
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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
Page 47 and 48: In some non-personal proper nouns,
Page 49 and 50: (i.e., not too complex) derivationa
Page 51 and 52: 2.2.4.5 Abbreviations and sentence
Page 53 and 54: Another case, where meaning bearing
Page 55 and 56: 2.2.4.6 The human factor: variation
Page 57 and 58: circumflex-) accented words without
Page 59 and 60: the tagger tries to identify a word
Page 61 and 62: xxxar-#1##AaiD######54578 endings-s
Page 63 and 64: "sombrancelha" N F P '=sobrancelha
Page 65 and 66: (6) Word class distribution and par
Page 67 and 68: VFIN 24.96 16 7.77 9 2.46 - - 25 3.
Page 69 and 70: the present participle by derivatio
Page 71 and 72: Inflexion tags combine with word cl
Page 73 and 74: 2.2.5.2 The individual word classes
Page 75 and 76: SPEC "specifiers": independent pron
Page 77 and 78: WORD FORM and LEXEME CATEGORIES gen
Page 79 and 80: WORD FORM and LEXEME CATEGORIES dea
Page 81 and 82: mood VFIN finite IND indicative SUB
Page 83 and 84: prefixal derivation in verbs comple
Page 85 and 86: graph. def. characteristics: hyphen
Page 87 and 88: PP prepositional group de=aluguel
Page 89 and 90: 2.2.5.3 Portuguese particles By ‘
Page 91 and 92: Deictic adverbs refer to discourse
Page 93 and 94: algo, algum=tanto, nada, nadinha?,
Page 95 and 96: quando når, da hvornår quanto [QU
Page 97: (1) Language distribution and error
Page 101 and 102: (4) "quando" conjunction or adverb
Page 103 and 104: oth for the simple ambiguities intr
Page 105 and 106: case of a 3.person possessor, the u
Page 107 and 108: The fact that these semantic distin
Page 109: In (Karlsson et. al, 1995:19ff) an
Page 112 and 113: meaning- scope someone loves everyb
Page 114 and 115: • 5. Tags can be integrated as me
Page 116 and 117: 19 0 0 - - - - >= 20 15 1 - - - - t
Page 118 and 119: Portuguese non-name words. Apart fr
Page 120 and 121: words: 40.8 10.5 17.9 2.9 0.5 3.1 8
Page 122 and 123: quite distinct, and few irregular e
Page 124 and 125: 3.3 Borderline ambiguity: The limit
Page 126 and 127: (5b) They [saw(see) [the girl with
Page 128 and 129: Choose 'saw', if within the same cl
Page 130 and 131: ambiguous words), moving them to "l
Page 132 and 133: (3) modernização "modernizar" N
Page 134 and 135: 3.5.1 Probabilistics: The 'fire a l
Page 136 and 137: In a brute force approach, for an a
Page 138 and 139: While undeniably involving more con
Page 140 and 141: Generative Grammar, introduced and
Page 142 and 143: node without branches matching the
Page 144 and 145: example is a grammar of one termina
Page 146 and 147: 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)
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antes/depois+de Depois [depois] AD
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While (2c-e) can be described as pr
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In (4d) ter ('have') does have mono
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When the potential subject is post-
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(1) Table: functions of pronominal
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ditador [ditador] N M S @N ‘-’
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In other contexts, para is not usua
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life that the work of different gra
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SPEC DET/SPEC ¬ @#FS/AS-N< artic
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4.6.3 Tree structures for constitue
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dono de restaurante que pilota a pr
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|-@N
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4.7 Elegant underspecification An i
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5 The uses of valency: A bridge fro
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Returning to a research view concer
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5.2 Valency instantiation: From sec
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Note that valency is treated as a f
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REMOVE (@%vt) (0 @%vK) (*1C @
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word order can't be counted on to m
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than by asking ‘is it an A?’ or
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hemisphere membership 218 , - ‘SW
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disambiguate the senses ‘suit’
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In all, the parser uses 16 atomic s
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‘+ uninferable positive feature +
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6.5 A semantic Constraint Grammar I
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capable - by “negative instantiat
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LIST = (@=c @=v @=p @=s @=t) ; LIS
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um verão ‘a summer’ * ok. * f
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An example of argument-head polysem
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The program module implementing the
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REMOVE (@=X) (*1 @%jn BARRIER @NON-
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@AUX, 'know how to, can' @MV, 'ta
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Note that the MT engine will choose
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Even where none of the semantic rul
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A casa revista PCP @N< revista PC
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O Itamarati +HUM @SUBJ The Itamara
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and a morphological CG module may c
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• V-trees - vertical tree structu
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descriptional complexity: 'full tag
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Here, each line of the CG-notation
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7.2 Grammar teaching on the Interne
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system's disposal. After acquiring
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the reach of "subject"-ness or "obj
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provided and what choices can be ma
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terminological confusion ? term not
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The tree structure of the sample se
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(5) Syntactic tree structures (VISL
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two function tags, since the studen
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7.3 Corpus research In the case of
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- 426 -
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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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