Download Word Classes.ppt

Word Classes
Laura A. Janda
Overview
1. How are word classes determined?
2. Who needs “particles”?
3. Is the “new vocative” in Russian a unique part of
speech?
2
Theoretical problems with particles as a
part of speech
•
•
•
3
Langacker (2013: 96) on parts of speech: “Traditional terms lack precise
definition, are inconsistent in their applications, and are generally
inadequate”
Croft (2001: 63-107) Parts of speech are partly language-specific: the
“same” categories might not coincide exactly across languages, though
the focal points of certain categories, such as noun, pronoun, verb are
typologically similar
Part of speech categories can be complex and can overlap:
verb
←
blestjaščie
glaza
‘shining eyes’
verb
←
budem
kušan’ki
‘we will eat’
participle
non-inflected
diminutive
→
adjective
blestjaščaja
pobeda
‘shining
victory’
→
noun
ja prigotovila
kušan’ki
‘I prepared
food’
Theoretical problems with particles as a
part of speech
•
•
•
Langacker (2013: 96) on parts of speech: “Traditional terms lack precise
definition, are inconsistent in their applications, and are generally
inadequate”
Croft (2001: 63-107) Parts of speech are partly language-specific: the
“same” categories might not coincide exactly across languages, though
the focal points of certain categories, such as noun, pronoun, verb are
typologically similar
Part of speech categories can be complex and can overlap:
Russian words classed as “particles”
are particularly prone to overlap across
part of speech categories
4
How do we identify parts of speech?
• Formal characteristics: morphological classes, e.g., nouns
inflected for case, verbs for tense and person
• Distributional characteristics: e.g., adpositions contiguous
with noun phrases, pronouns substitute for nouns,
conjunctions bind phrases
• Semantic characteristics: e.g., nouns signify entities, verbs
signify situations
Ideally, a classification should take into consideration all three
types of characteristics
5
How do we identify parts of speech?
• Formal characteristics: morphological classes, e.g., nouns
inflected for case, verbs for tense and person
• Distributional characteristics: e.g., adpositions contiguous
with noun phrases, pronouns substitute for nouns,
conjunctions bind phrases
• Semantic characteristics: e.g., nouns signify entities, verbs
signify situations
Russian
words
classed
as
“particles”
Ideally, a classification should take into consideration all three
a coherent definition for formal,
types oflack
characteristics
distributional and semantic
characteristics
6
2. Who needs “particles”?
• In 1985, Zwicky argued that “particle” is a
pretheoretical notion that should be eliminated
from linguistic analysis. We propose a
reclassification of Russian particles that
implements Zwicky’s directive. The so-called
particles lack a coherent conceptual basis as a
category and many of them are ambiguous
since they can also be classed as adverbs,
conjunctions, predicatives and other parts of
speech.
7
Particles: Russian ЖЕ (ŽE)
Konečno, sgorel – nel’za že
v polden’ ležat’ na solncepeke
[«Domovoj», 2002]
‘Of course, you got a sunburn! You
can’t ŽE lie in the hot sun in the
middle of the day!’
“You are wrong! And more than
that, you are capable of arriving
at the correct conclusion yourself,
but nevertheless you are sticking
to the wrong conclusion.” McCoy
(2003: 125)
8
Particles: Russian ЖЕ (ŽE)
•
Konečno, sgorel – nel’za že
v polden’ ležat’ na solncepeke
[«Domovoj», 2002]
‘Of course, you got a sunburn! You
•
can’t ŽE lie in the hot sun in the
middle of the day!’
Small uninflected words lacking
referential content (Švedova et al.
1980)
Meaning: modal and pragmatic
attitudes towards a proposition
“You are wrong! And more than
• Multifunctional  allow multiple
that, you are capable of arriving
interpretations
at the correct conclusion yourself,
but nevertheless you are sticking
• Overlap
with other parts of speech
to the wrong conclusion.”
McCoy
(adverbs, conjunctions,
(2003: 125)
interjections, predicatives)
• A part of speech
?
9
Particles: small words, big problems
• “The wide use of particles is a typical feature of colloquial
Russian” (Vasilyeva 1972: 6)
Emu ja mogu poverit’ – ‘I can trust him’
Ved’ emu ja mogu poverit’ – ‘I can trust him, you know this’
Emu-to ja mogu poverit’ – ‘I know, I can trust him’
Emu ja ešče mogu poverit’ – ‘Well, I suppose, I can trust him’
Tak emu ja mogu poverit’ – ‘so I can trust him’
Vot emu ja mogu poverit’ – ‘He is the one I can trust’
Emu ja i mogu poverit’ – ‘Therefore I can trust him’
Da emu ja mogu poverit’ – ‘Well, I can surely trust him’
Xot’ emu ja mogu poverit’ – ‘At least I can trust him’
10
Particles: small words, big problems
• Active use of particles distinguishes L1 speakers from L2 learners
(Nikolaeva 1985: 7)
• Relevant for other languages too.
• Heinrichs, W. 1981. Die Modalpartkeln im Deutschen und
Schwedischen. Tübingen.
• L2 German speaker:
– Bitte geben Sie mir das Buch.
• L1 German speaker:
– Können Sie nur vielleicht mal das Buch da geben?
– Ach, geben Sie nur doch bitte mal das Buch.
11
Outline
• Particles in Russian
– Extent
– Distribution in the corpus
• Our data: 9 words
– Database
• Analysis
– Alternative annotation scheme & guidelines
• Experiments 1 and 2
– Training a tagger to disambiguate between uses
12
Practical problems with particles as a
part of speech
•
•
•
•
13
Automatic Part of Speech taggers are trained on a gold standard corpus
1 Part of Speech error can foul up the parsing of a whole sentence
Manning 2011: Penn Treebank of English yields 97% accuracy in
automatic Part of Speech tagging, but
– This yields only 57% sentence parsing accuracy!
– Main culprit is Part of Speech tagging errors
Accurate tagging is important not only for Natural Language Processing,
but for all tools sourced by NLP:
– spelling and grammar checkers
– intelligent computer-assisted language learning
– linguistic corpora
– machine translation
Practical problems with particles as a
part of speech
•
•
•
•
Automatic Part of Speech taggers are trained on a gold standard corpus
1 Part of Speech error can foul up the parsing of a whole sentence
Manning 2011: Penn Treebank of English yields 97% accuracy in
automatic Part of Speech tagging, but
– This yields only 57% sentence parsing accuracy!
– Main culprit is Part of Speech tagging errors
Accurate tagging is important not only for Natural Language Processing,
but for all tools sourced by NLP:
– spelling and grammar checkers
– intelligent computer-assisted language learning
– linguistic corpora
– machine translation
Russian words classed as “particles”
are the most error-prone part of speech
14
Our proposal
•
•
•
•
Particle is not a valid category.
Russian particles have no
coherent profile.
“Particle” looks like a garbage
category that is used when one
feels uncertain about how to
classify a word.
Particle is not a classification but
rather a failure to classify a word.
•
•
•
It is possible to reclassify the
words commonly classed as
“particles”.
We offer improved annotation
guidelines that eliminate the
class of particles altogether.
Descriptively more precise
analysis.
15
Extent of particles in Russian
Estimates of the number of Russian particles vary:
• Zaliznjak (1980) designates over 100 Russian words as particles.
• Nikolaeva (1985: 8) lists the following alternative counts:
– 131 particles in the 17-volume Academy dictionary
– 110 particles in the 4-volume Academy dictionary
– 84 particles in Ušakov’s dictionary
– 75 particles in Ožegov’s dictionary
• Starodumova (1997: 8-9) claims that Russian is among the
most “particle-rich” languages in the world, with
approximately 300 particles.
16
Parts of speech in the disambiguated subcorpus of Russian
Part of speech
# tokens in RNC
% tokens in RNC
S (noun)
1,707,312
28.7%
V (verb)
1,007,526
16.9%
SPRO+APRO+PRAEDICPRO+ADVPRO
(pronoun)
875,142
14.7%
PR (preposition)
612,857
10.5%
A (adjective)
506,691
8.5%
CONJ (conjunction)
471,275
7.9%
PART (particle)
268,139
4.5%
ADV (adverb)
426,367
4.1%
NUM+ANUM (numeral)
126,567
2.1%
PRAEDIC (predicative)
42,318
0.7%
PARENTH (parenthetical)
25,891
0.4%
8,377
0.1%
5,944,156
99.1%
INTJ (interjection)
Sum
17
Extent of part-of-speech ambiguity in particles
Type
Part of speech
Unambiguous
2-way
ambiguity
3-way
ambiguity
4-way
ambiguity
18
# of lexemes
Example
-
54
vot
Conjunction
28
ved’
Adverb
17
ešče
Predicative
7
net
Interjection
8
nu
Parenthetical
4
požaluj
Preposition
1
vrode
Adverb, Predicative
5
prosto
Adverb, Conjunction
5
poka
Parenthetical, Predicative
1
spasibo
Parenthetical, Adverb
1
nikak
Parenthetical, Adverb, Predicative
1
xorošo
Parenthetical, Adverb, Conjunction
1
točno
Data:
9 particles with one additional part-of-speech reading
Lexeme Gloss
Frequency Adverb Conjunction
RNC
ešče
‘more, yet’
14,765
ADV
PART
tak
‘so’
22,093
ADV
PART
ved’
‘you know’
5,149
CNJ
PART
slovno
‘like, as if’
1,369
CNJ
PART
daže
‘even’
8,562
CNJ
PART
že
‘after all’
21,350
CNJ
PART
li
‘if’
7,708
CNJ
PART
da
‘yes, and, but’
12,280
CNJ
PART
net
‘no, there is no’
9,786
Database:
100 random sentences for each word
900 rows in Excel spreadsheet
19
Predicative Particle
PRED
PART
Source of data:
disambiguated part of the Russian
National Corpus (gold standard RNC)
Can we re-tag the uses of these lexemes and avoid the tag ‘particle’?
Analysis:
Particle-free annotation
Lexeme
Gloss
ešče
‘more,
yet’
ADV
CNJADV
tak
‘so’
ADV
CNJADV
CNJSUB
ved’
‘you
know’
ADV
CNJADV
CNJSUB
ADV
CNJADV
ADV
CNJCOO
slovno ‘like, as if’
20
Adverb
Conjunction Predicative
daže
‘even’
že
‘after all’
li
‘if’
ADV
CNJCOO
CNJSUB
da
‘yes, and,
but’
ADV
CNJCOO
net
‘no, there
is no’
Interjection Emphasizer
Question
word
INTJ
CNJADV
CNJCOO
EMPH
QST
PRED
VMOD
INTJ
NEST
PRED
INTJ
Analysis:
Particle-free annotation
Lexeme
Gloss
ešče
‘more,
yet’
ADV
CNJADV
tak
‘so’
ADV
CNJADV
CNJSUB
ved’
‘you
know’
ADV
CNJADV
CNJSUB
ADV
CNJADV
ADV
CNJCOO
slovno ‘like, as if’
21
Adverb
Conjunction Predicative
daže
‘even’
že
‘after all’
li
‘if’
ADV
CNJCOO
CNJSUB
da
‘yes, and,
but’
ADV
CNJCOO
net
‘no, there
is no’
Interjection Emphasizer
Question
word
INTJ
CNJADV
CNJCOO
EMPH
QST
PRED
VMOD
INTJ
NEST
PRED
INTJ
Analysis: Particle ЖЕ (ŽE)
1. Adverbial conjunction (ADVCNJ) – syntactically optional, usually preposed.
13%
Konečno, sgorel – nel’za že v polden’ ležat’ na solncepeke.
‘Of course, you got a sunburn! After all, you can’t lie in the hot sun in the
middle of the day!’
2. Coordinating conjunction (CNJCOO) – usually postposed, obligatory for
creating an explicit contrast between syntactic constituents:
Satira i jumor. Odni ix rezko razdeljajut ... , drugie že vidjat v jumore ...
raznovidnost’ satiry.
‘Satire and humor: some people keep them strictly distinct ... , others 6%
however see humor as a form of satire.’
3. Emphasizer (EMPH) – syntactically optional, follows a phrasal stress-bearing
word and brings it in focus of attention
Seli s kraju ― i tut že iz veščmeška Vovka izvlek butylku portvejna.
‘They sat down ― and right away then Vovka pulled a bottle of
portwine
out of the supply bag.’
81%
22
Analysis: Particle ДА (DA)
1. Interjection – ‘yes’
50%
Da, zavtra ja priedu. ‘Yes, I will come tomorrow’
2. Coordinating conjunction – ‘and’, ‘but’
25%
Ded da baba ‘grandfather and grandmother’
3. Adverb – ‘after all, well’
19%
Da v etix pal’to pol goroda xodit! ‘Well, half of the town is wearing
these coats!’
4. Predicative – stands for entire proposition, carries stress:
3%
Neobxodimo ustanovit’, želaet li on vozvratit’sja. Esli da, to kogda.
‘It is necessary to find out whether he wants to come back. If so, when’.
5. Modal verb – unstressed, used with imperatives, infinitives, present
tense finite forms:
Da budet svet! ‘Let there be light!’
3%
23
Experiment 1: How badly does tagging of
Russian particles perform?
• Source: Russian National Corpus gold standard, using the
tags manually assigned there
• Database: 100 randomly-selected sentences for each of
nine high-frequency particles (= 900 sentences)
• Method: Hidden Markov Model (HMM), 10-fold crossvalidation, each time using 90 sentences as training set
and 10 sentences as test set
We measure performance as
improvement in accuracy
(correct guesses/total guesses) over baseline
(frequency of most common tag for each word)
24
Experiment 1: How badly does tagging of
Russian particles perform?
• Source: Russian National Corpus gold standard, using the
tags manually assigned there
• Database: 100 randomly-selected sentences for each of
nine high-frequency particles (= 900 sentences)
• Method: Hidden Markov Model (HMM), 10-fold crossvalidation, each time using 90 sentences as training set
and 10 sentences as test set
We measure performance as
improvement in accuracy
(correct guesses/total guesses) over baseline
(frequency of most common tag for each word)
25
Distribution of tags across the 900 sentences
according to the RNC gold standard
Lexeme
ADV
(adverb)
CNJ
(conjunction)
ešče
83
tak
101
PRAEDIC
(predicative)
PART
(particle)
Total
examples
17
0
100
101
ved’
33
67
100
slovno
83
17
100
daže
16
84
100
že
6
94
100
li
18
82
100
da
54
46
100
42
100
net
58
Most common tag taken as “baseline” for each word
26
Experiment 1: So how did the HMM tagger do?
Lexeme
ešče
tak
ved’
slovno
daže
že
li
da
net
27
Baseline
83%
100%
67%
83%
84%
94%
82%
54%
58%
Average
accuracy
70%
100%
78%
89%
90%
89%
76%
75%
89%
Gain over
Baseline
-13%
0%
11%
6%
6%
-5%
-6%
21%
31%
Experiment 1: So how did the HMM tagger do?
еščё
tak
ved’
slovno
Average accuracy
daže
Baseline
že
li
da
net
28 0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Experiment 1: So how did the HMM tagger do?
еščё
tak
ved’
slovno
Average accuracy
daže
Baseline
že
li
da
net
29 0%
Total gain: 51%
These results confirm our suspicion that the
tagging of Russian “particles” in the RNC gold
standard is not consistent
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Experiment 2: Life without particles
• Same source, database, and method as Experiment 1, but
using our tags for the nine words instead of those in the
RNC gold standard
30
Distribution of tags across the 900 sentences
according to our tagging scheme
ADV
(adverb)
CNJ
(conjunction)
ešče
ADV 100%
tak
ADV
85%
ADV
57%
ADV
49%
ADV
85%
CNJADV
0%
CNJADV 7%
CNJSUB 8%
CNJADV 33%
CNJSUB 10%
CNJADV 51%
ved’
slovno
daže
že
li
ADV 23%
da
ADV
19%
net
31
PRAEDIC
(predicative)
INTJ
(interjection)
EMPH
(emphasizer)
QST
(question word)
INTJ 1%
CNJCOO 15%
CNJADV 13%
CNJCOO 6%
CNJCOO 6%
CNJSUB 0%
CNJCOO 25%
EMPH 81%
QST 71%
PRAEDIC 3%
VMOD 3%
NEST 60%
PRAEDIC
10%
INTJ 50%
INTJ 30%
Experiment 2: So how did the HMM tagger do?
Lexeme
ešče
tak
ved’
slovno
daže
že
li
da
net
32
Baseline
100%
85%
57%
51%
85%
81%
71%
50%
60%
Average
accuracy
100%
90%
80%
68%
86%
76%
85%
79%
89%
Gain over
Baseline
0%
5%
23%
17%
1%
-5%
14%
29%
29%
Experiment 2: So how did the HMM tagger do?
еščё
tak
ved’
slovno
Average accuracy
daže
Baseline
že
li
da
net
33
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Experiment 2: So how did the HMM tagger do?
еščё
tak
ved’
slovno
Average accuracy
daže
Baseline
Total gain: 127%
More than twice the gain over baseline
as in Experiment 1,
despite much more complex tagging scheme
že
li
da
net
34
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Conclusions
35
•
Can we eliminate particles from the part-of-speech classification in
Russian?
– Yes, “particle” is not a classification but a failure to classify a word.
– It is possible to reclassify the words commonly classed as “particles”.
•
What are the practical benefits of this approach?
– Particle-free annotation, where all categories are meaningful and
useful for further applications.
– Analysis that is descriptively more precise.
•
Our methods
– Usage-based analysis of corpus data: 9 high-frequency “particles”.
– Experiment: training an automatic tagger to disambiguate uses.
3. Is the “new vocative” in Russian a unique
part of speech?
36
THEORY
PART ONE: What is a vocative?
A call for attention that hasn’t gotten much attention
37
Vocatives have been largely ignored
“even though they are amongst the most basic and earliest
acquired structures of language, vocatives have hardly
ever been discussed in all their facets from a linguistic point
of view” Sonnenhauser & Hanna 2013: 3
Among the few studies: Fink 1972, Zwicky 1974, Levinson
1983, Greenberg 1996
However, this situation seems to be changing:
Sonnenhauser & Hanna 2013, Hill 2014, Julien 2014
38
Is a vocative a case form of a noun?
YES, the vocative:
– Can have distinct morphological form (Kiparsky 1967)
– Can often be replaced by nominative, which is a case
– Can show agreement within the NP (Hill 2014, Julien 2014)
– Can be syntactically integrated via a Vocative Phrase (Hill 2014)
NO, the vocative:
– Is not syntactically integrated into a clause (Isačenko 1962)
– Has peculiar restrictions that do not apply to other cases
(functional, lexical, morphological, phonological, cf. Andersen 2012)
– Diachronically behaves differently (cf. Bulgarian & Macedonian lost
all cases but kept vocative)
39
Is a vocative a form of a verb?
YES, the vocative:
– Marks 2nd person (Fink 1972)
– Shares features with imperatives (Jakobson 1971,
Greenberg 1996)
– Possessive predicational vocatives (Din idiot! ‘You
idiot! [lit. Your idiot]’ ≈ Du er en idiot ‘You are an idiot’,
cf. Julien 2014)
NO, the vocative would be a mighty defective verb…
40
Is a vocative a form of a verb?
YES, the vocative:
From the perspective of Russian and
Saami,(Fink
interpretation
as a verb
– MarksNorth
2nd person
1972)
is unlikely,
so imperatives
we won’t pursue
that 1971,
– Shares features
with
(Jakobson
Greenberg 1996) avenue here
– Possessive predicational vocatives (Din idiot! ‘You
idiot! [lit. Your idiot]’ ≈ Du er en idiot ‘You are an idiot’,
cf. Julien 2014)
NOTE: association
with possessive
NO, the vocative would be a mighty defective verb…
41
Is a vocative another part of speech?
Andersen (2012) argues that the
vocative is a separate part of
speech, based on evidence from
the Russian “new” vocative
Segue to Russian
42
PART TWO: Russian “new” vocative
(1) Dissyllabic hypocoristics. (Костя! ⇒) Кость!, (Надя! ⇒) Надь!;
(2) Dissyllabic diminutives. (Ванька! ⇒) Ваньк!, (Машка! ⇒) Машк!;
(3) Hypocoristics of three or more syllables. (Наташа! ⇒) Наташ!, (Сережка!
⇒) Сережк!, ...;
(4) Kinship terms. (дядя! ⇒) дядь!, (мама! ⇒) мам!,...;
(5) Patronymics. (Андреевна! ⇒) Андреевн!, (Николаевна! ⇒) Николавн!,...;
(6) Name + patronymic. (Анна Иванвовна! ⇒ Анн Ванна! ⇒) Анн Ванн!, (Марья
Александровна! ⇒ Марь Санна! ⇒) Марь Санн!, ...;
(7) Common nouns. (девушка! ‘Miss’ ⇒) девушк!, (хозяйка! ‘hostess, landlady’
⇒) хозяйк!, (ребята! ‘boys, guys’ ⇒) ребят!, (девчата! ‘girls’ ⇒) девчат!, ....
BOLDFACE marks items that conflict with Russian phonotactics
(Examples from Andersen 2012)
43
Final voicing seems to be on its way out,
and
not
all
speakers
accept
vocatives
PART TWO: Russian “new” vocative
with consonant clusters that are
unusual
for Russian
(Daniel’
(1) Dissyllabic hypocoristics. (Костя!
⇒) Кость!,
(Надя! ⇒)
Надь!; 2009)
(2) Dissyllabic diminutives. (Ванька! ⇒) Ваньк!, (Машка! ⇒) Машк!;
(3) Hypocoristics of three or more syllables. (Наташа! ⇒) Наташ!, (Сережка!
⇒) Сережк!, ...;
(4) Kinship terms. (дядя! ⇒) дядь!, (мама! ⇒) мам!,...;
(5) Patronymics. (Андреевна! ⇒) Андреевн!, (Николаевна! ⇒) Николавн!,...;
(6) Name + patronymic. (Анна Иванвовна! ⇒ Анн Ванна! ⇒) Анн Ванн!, (Марья
Александровна! ⇒ Марь Санна! ⇒) Марь Санн!, ...;
(7) Common nouns. (девушка! ‘Miss’ ⇒) девушк!, (хозяйка! ‘hostess, landlady’
⇒) хозяйк!, (ребята! ‘boys, guys’ ⇒) ребят!, (девчата! ‘girls’ ⇒) девчат!, ....
BOLDFACE marks items that conflict with Russian phonotactics
(Examples from Andersen 2012)
44
Features of Russian “new” vocative that
Andersen uses to argue that vocative is not a case
• Pragmatic restrictions: Function is primarily pragmatic, not
syntactic
• Lexical restrictions: Only with forms of address
• Syntactic restrictions: Syntactically independent of sentence
• Morphophonological restrictions: Limited to words ending in –
a with penultimate or prepenultimate stress
• Phonological peculiarities: Formed by truncation, resulting in
word-final consonant clusters (lacking vowel insertion) and
voiced final consonants not otherwise tolerated in Russian
• Strong association with diminutives (themselves peculiar)
45
Features of Russian “new” vocative that
Andersen uses to argue that vocative is not a case
• Pragmatic restrictions: Function is primarily pragmatic, not
syntactic
• Lexical restrictions: Only with forms of address
But Syntactically
do these (and
other) of sentence
• Syntactic restrictions:
independent
arguments
against
calling
• Morphophonological
restrictions:
Limited
to words ending in –
vocative
a case really
hold?
a with penultimate
or prepenultimate
stress
• Phonological peculiarities: Formed by truncation, resulting in
word-final consonant clusters (lacking vowel insertion) and
voiced final consonants not otherwise tolerated in Russian
• Strong association with diminutives (themselves peculiar)
46
Pragmatic restrictions
Other examples of cases used to express pragmatic functions:
• Virile vs. deprecatory endings for Npl in Polish (Janda 1996)
-owie
’-i <soft cons + -y>
-y
[honorific virile]
[neutral virile]
[non-virile]
profesorowie
profesorzy
profesory
‘professors’ [wow, I
respect those men!]
‘professors’ [they
are men]
‘professors’ [they
are wimps, not men]
• Ethical dative (Janda 1993, Janda & Clancy 2006)
Cz: Pustila jsem dceru na hory a ona ti si mi zlomila nohu!
‘I let my daughter go to the mountains and she you-DAT self-DAT me-DAT broke leg!’
[you-DAT: I’m telling you, can you believe it?!]
[self-DAT: It’s her leg, she did it to herself.]
[me-DAT: Just imagine what this means for me, I’m going to suffer for this!!]
47
Pragmatic restrictions
Other examples of cases used to express pragmatic functions:
• Virile vs. deprecatory endings for Npl in Polish (Janda 1996)
Notice
that the
ethical
datives
are also
-owie
’-i <soft
cons + -y>
-y
[honorific
virile]
[neutral integrated
virile]
[non-virile]
not syntactically
into the
profesorowie
profesorzy
profesory
sentence ‘professors’ [they
‘professors’ [wow, I
‘professors’ [they
respect those men!]
are men]
are wimps, not men]
• Ethical dative (Janda 1983, Janda & Clancy 2006)
Cz: Pustila jsem dceru na hory a ona ti si mi zlomila nohu!
‘I let my daughter go to the mountains and she you-DAT self-DAT me-DAT broke leg!’
[you-DAT: I’m telling you, can you believe it?!]
[self-DAT: It’s her leg, she did it to herself.]
[me-DAT: Just imagine what this means for me, I’m going to suffer for this!!]
48
Lexical restrictions
There is plenty of evidence of lexical restrictions on case forms:
•
Loc 2 in Russian, as in в снегý ‘in the snow’:
– this case ending is largely restricted to nouns designating concrete
locations (“жесткая локализация”, Plungjan 2002)
– an alternate ending for 148 nouns, primarily monosyllabic masculine
animate nouns with mobile stem stress (Janda 1996)
•
Gen 2 in Russian, as in выпить чаю ‘drink (some) tea’:
– used with only about 1% of masculine inanimate nouns
– used with nouns referring to quantifiable substances (Worth 1984;
Janda 1996)
– currently productive, cf. абрикотин ‘apricot liquor’, анилин ‘aniline’,
асбест ‘asbestos’…
49
Morphophonological restrictions
There is plenty of evidence of morphophonological restrictions on case forms:
• Loc 2 in Russian, as in в снегý ‘in the snow’:
– primarily monosyllabic masculine animate nouns with mobile stem stress
– there are ten nouns with polysyllabic Nsg forms, but most of these derive
from monosyllabic stems via pleophony (bergъ > берег, берегý),
diminutive formation (бок, бокý ‘side’ has diminutive бочок, бочкý), or
prefixation (cf. порт, портý ‘port’ and аэропорт, аэропортý ‘airport’)
(Janda 1996)
•
50
NPl –á, as in берег, берегá ‘bank’
– possible only for nouns with accentual patterns that permit end stress in the
N(A)pl as opposed to stem stress in the singular (only two exceptions to this
rule – two nouns with fixed end stress: рукав, рукавá ‘sleeve’; обшлаг,
обшлагá ‘cuff’)
– also restricted largely to words that result from pleophony or partially imitate
the segmental phonology of pleophonic forms (потрох, потрохá ‘entrail’;
соболь, соболя ‘sable’) (Janda 1996, Worth 1983)
Phonological peculiarities
There is plenty of evidence of phonological peculiarities in case forms:
• Bethin 2012 “Reduction of unstressed /o/ and /a/ to [ɐ] or [ə] after
non-palatalized consonants and to [ɪ] after palatalized ones in
Contemporary Standard Russian (CSR) is systematic. But in certain
inflectional suffixes [ə] occurs instead of the expected [ɪ] after
palatalized consonants.”
– For example, the last vowel in дядя ‘uncle’ should be [ɪ], but it is
[ə], despite the fact that this runs counter to prevailing иканье in
Contemporary Standard Russian
51
Diachronic peculiarities
Cases are lost in different orders, and it is not really true that vocative was
preserved while all other cases were lost in Bulgarian & Macedonian
•
•
•
52
The vocative is marginal and optional in both Bulgarian (Girvin 2013) and
Macedonian (Friedman 1993)
The original Slavic vocative was lost in some Slavic languages where all
other cases were preserved (Russian, for example)
There is just a lot of variation that doesn’t tell us anything about whether or
not vocative is a case
References
53