LET THE DATA SPEAK FOR THEMSELVES: A FORM-DRIVEN CROSS ...

LET THE DATA SPEAK FOR THEMSELVES: A FORM-DRIVEN CROSS-LINGUISTIC STUDY OF TENSE AND ASPECT

CHOU MO (C.MO@UU.NL)

15, JUNE, 2018

UIL OTS, UTRECHT UNIVERSITY Research Questions ? How are the different tense notions expressed in an aspect-prominent language like Mandarin? ? What are the similarities and differences between the temporal systems of tense-prominent and aspect-prominent languages?

Step 2: Translation Distance Calculation

Example No. French German Dutch Spanish English Mandarin

Mandarin Aspect Markers (Xiao & McEnery, 2004: 171, 240):

(I) Perfective Aspect Markers ? Le: actual marker, e.g. chi-le `eat-le'. (Verbal le vs. Sentential le) ? Guo: experiential marker, e.g. kan-guo `see-guo'. ? RVC: completive marker, structure `simple verb form + resultative complement (verb/adj.)', e.g. xie-hao `write-done', chi-wan `eat-finish'. The complement indicates the result of an action. ? Unmarked duplication: delimitative marker, simple verbal form is duplicated, e.g. yao-yao `shake-shake'. (II) Imperfective Aspect Markers ? Zhe: a progressive/state marker, e.g. baoliu-zhe `keep-zhe', and wo-zhe `hold-zhe'. ? Zai: a progressive marker, e.g. zai-jixu `zai-continue'. (III) Zero Form ? Aspectually unmarked verb: simple verb form, e.g. xunzhao `look for'. Perfective or Imperfective, dependent on context.

Methodology (computational methodology from van der Klis et al. (2017)) Parallel Corpus Data (French, German, Dutch, Spanish, English, Mandarin) Chapters 1-3 in French novel L'?tranger (app. 300 sentence examples) Chapters 1 & 17 in English novel Harry Potter and the Sorcerer's Stone (app. 1000 sentence examples) Step 1: Sentence Tense/Aspect Marker Annotation Example No. 24950 French: J' ai bu. (pass? compos?) German: Ich habe getrunken . (perfekt) Dutch: Ik dronk. (o.v.t.) Spanish: Beb?. (pret?rito indefinido) English: I drank. (simple past) Mandarin: (he-le `drink-le') (le) Tense/Aspect Tuple No. 24950 :

French Map

German Map

24950

pass? perfekt o.v.t. pret?rito simple

le

compos?

indefinido past

25851

pass? perfekt v.t.t. pret?rito simple

le

compos?

perfecto present

compuesto

Tense/Aspect

0

0

1

1

1

0

Variation

Total tense/aspect variation between 2 examples Translation distance =

Number of languages in comparison

Total variation: 3 (0+0+1+1+1+0); 6 languages are compared. The translation distance between Examples 24950 and 25851 is 3/6 (0.5).

Descriptive statistics are collected: Tense/aspect marker frequency & tuple frequency

Aspect Form unmarked

le rvc duplication zhe non-verb guo zai

Frequency 154

77 50 11 9 5 2 2

Percentage

49.7% 24.8% 16.1% 3.5% 2.9% 1.6% 0.6% 0.6%

Aspect Pt Pt Pre Pt

Form Nart1 Impf

Cont

unmarked 59 42 19 13

Le

31 12 3

0

rvc

20 4 0

0

duplication 10 0 0

0

zhe

6 40

4

non-verb 2 21 3

0

zai

0 00

4

Mandanrin Aspect Form Distribution in Camus dataset

Step 3: Multi-dimensional Maps (Smaller Translation Distance, Closer Dots )

Dutch Map

Spanish Map

TABUDAG 2018

`Time in Translation' group (Henri?tte de Swart, Bert Le Bruyn, Martijn van der Klis) See 'Time in Translation' Project at

Top 4 EU language Tuples in Camus Dataset Pt Nart 1 (Past narrative): Perfekt, simple past, pret?rito indefinido, pass? compos?, ovt Pt Impf (Past imperfective): Pr?teritum, simple past, pret?rito imperfecto, imparfait, ovt Pre (PRESENT): Pr?sens, simple present, presente, pr?sent, ott Pt Cont (Past continous) : pr?teritum, past continuous, pret?rito imperfecto, imparfait, ovt

Mandarin Aspect Form Distribution (among Top 4 EU language tuples in Camus Dataset) ? Unmarked: Pt Nart 1 > Pt Impf > PRESENT> Pt Cont ? Le: Pt Nart 1 > Pt Impf > PRESENT> Pt Cont=0 ? Rvc: Pt Nart 1 > Pt Impf > PRESENT= Pt Cont=0 ? Duplication: Pt Nart 1 > Pt Impf=PRESENT= Pt Cont=0 ? Zhe: Pt Nart 1 > Pt Impf > Pt Cont > PRESENT=0 ? Non-verb: Pt Impf > PRESENT > Pt Nart 1 > Pt Cont=0 ? Zai: Pt Cont> Pt Nart 1 = Pt Impf = PRESENT=0 * Guo: only 5 examples, co-occur with either PERFECT or PLUPERFECT tuples.

Subset theory for EU PERFECT (see MDS Maps) Perfect use in EnglishPerfect use in Spanish Perfect use in Dutch Perfect use in GermanPerfect use in French (de Swart, 2017)

Mandanrin Aspect Distributon in PERFECT vs. PAST Competition

German [+Narration]

PERFECT

PAST

Unmarked, le, rvc, zhe,

Unmarked (3rvc, 2non-verb)

duplication (guo, zai, non-verb)

Dutch [+Boundedness] Spanish [+Deictic adverbs]

English [+Classical Perfect]

Le, unmarked (guo,1zhe)

Le, unmarked (guo, 1non-verb,1rvc) Le, unmarked (guo, 3non-verb,1zhe)

Unmarked, le, rvc, zhe, duplication (zai, non-verb) Unmarked, le, rvc, zhe, duplication(zai, non-verb)

Unmarked, le, rvc, zhe, duplication (zai, non-verb)

English Map

Mandarin Map

Aspect Marker

unmarked

rvc

le1 (verbal le)

le12 (mix le)

Pt Nart 2 Count Percentage 142 46.41%

63 20.59% 41 13.40%

22 7.19%

PRESENT

Pt Impf

Pt Nart 3

Pt Cont

Count Percentage Count Percentage Count Percentage Count Percentage

62

66.67% 52 55.91% 16 57.14% 13 52.00%

2

2.15% 7

7.53%

1

3.57%

1

4.00%

2

2.15%

3

3.23%

7 25.00% 5

20.00%

11

11.83% 4

4.30%

2

7.14%

0

0.00%

IMPERATIVE

PLUPERFECT

FUTURE

Count Percentage Count Percentage Count Percentage

5

45.45% 0

0.00%

0

0.00%

4

36.36% 3 33.33%

0

0.00%

0

0.00%

1 11.11%

0

0.00%

0

0.00%

0

0.00%

0

0.00%

Duplication 14 4.58%

1

1.08%

0

0.00%

0

0.00%

0

0.00%

1

9.09%

0

0.00%

0

0.00%

zhe

14 4.58%

1

1.08%

4

4.30%

0

0.00%

5

20.00%

0

0.00%

0

0.00%

0

0.00%

non-verb 9

2.94%

11

11.83% 22 23.66% 2

7.14%

0

0.00%

1

9.09%

0

0.00%

0

0.00%

zai

1

0.33%

2

2.15%

0

0.00%

0

0.00%

0

0.00%

0

0.00%

0

0.00%

0

0.00%

Aux

0

0.00%

1

1.08%

1

1.08%

0

0.00%

1

4.00%

0

0.00%

0

0.00%

4 100.00%

guo

0

0.00%

0

0.00%

0

0.00%

0

0.00%

0

0.00%

0

0.00%

5 55.56%

0

0.00%

Sum

306 100.00%

93

100.00% 93 100.00% 28 100.00% 25 100.00% 11 100.00% 5 100.00% 4 100.00%

Top 8 EU language tuples in Harry Potter Dataset

Conclusions from 2 Datasets

Pt Nart 2: Pr?teritum, simple past, pret?rito indefinido, pass? simple, ovt

? EU languages distinguish PAST/PRESENT/FUTURE ,

PRESENT: Pr?sens, simple present, presente, pr?sent, ott

Mandarin distinguishes FUTURE/NON-FUTURE (Aux can

Pt Impf: Pr?teritum, simple past, pret?rito imperfecto, imparfait, ovt

mark FUTURE) , but not PAST/PRESENT.

Pt Nart 3: Perfekt, simple past, pret?rito indefinido, pass? compos?, vtt

? In EU languages, (almost) no variation in PLUPERFECT,

Pt Cont: Pr?teritum, past continuous, pret?rito imperfecto, imparfait, ovt

PRESENT and FUTURE, but competition in PAST and

IMPERATIVE: Imperativ, imperative, imperativo, imp?ratif, imperatief

PERFECT domains.

PLUPERFECT: Plusquamperfekt, past perfect, pret?rito pluscuamperfecto, plus-que-parfait, vvt ? Mandarin has rich forms for PAST & PRESENT, but

FUTURE: Futur I, simple future, futuro pr?ximo, futur proche, ott

restricted forms for PLUPERFECT & FUTURE, both of which

Mandarin Aspect Form Distribution (among Top 8 EU language tuples in Harry Potter Dataset) ? Unamrked: Pt Nart 2 > PRESENT> Pt Impf >Pt Nart 3>Pt Cont >IMPERATIVE ? Rvc: Pt Nart 2 > Pt Impf > IMPERATIVE>PLUPERFECT> PRESENT>Pt Nart 3=Pt Cont ? Le1 (verbal le): Pt Nart 2> Pt Nart 3 > Pt Cont >Pt Impf > PRESENT> PLUPERFECT ? Le12 (mix le): Pt Nart 2 > PRESENT > Pt Impf > Pt Nart 3 (>Pt Cont=0) ? Non-verb: Pt Impf > PRESENT> Pt Nart 2> Pt Nart 3 >IMPERATIVE (>Pt Cont=0) ? Aux: FUTURE > PRESENT= Pt Impf = Pt Cont ? Zhe: Pt Nart 2 > Pt Cont >Pt Impf > PRESENT ? Duplication: Pt Nart 2> PRESENT=IMPERATIVE ? Zai: PRESENT>Pt Nart 2 ? Guo: PLUPERFECT

must be marked in Mandarin. ? Iceberg in Mandarin aspect research: unmarked (50% data, Pt Nart > Pt Impf > Pt Cont), rvc (Pt Nart > PRESENT) . ? Verbal le: Pt Nart > Pt Impf > PRESENT, but also in Pt Cont. (why?) Sentential le: Pt Nart > PRESENT > Pt Impf ? Duplication: Pt Nart (V-le-V), PRESENT, IMPERATIVE (V-V) ? Zhe: Pt Nart > Pt Impf > PRESENT ? Zai: few in Narration, more imperfective than zhe ? Guo: reside within European PERFECT & PLUPERFECT ? Non-verb: prefer strong imperfective contexts

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