Introduction

Issues and Solutions

Conclusion

References

UD-Tatar NMCTT Treebank:Issues in Annotation across Turkic UD
Chihiro Taguchi
Natural Language Processing Group
Department of Computer Science and Engineering, University of Notre Dame
https://ctaguchi.github.io

September 8, 2023

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Introduction

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OutlineIntroduction
Issues and Solutions
Tokenization
Part-of-speech
Morphology
Conclusion

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Introduction

Issues and Solutions

Conclusion

References

Introduction

This report:• introduces UD Tatar NMCTT Treebank• Discusses annotation disagreements across Turkic UD treebanks, with a
special focus on Tatar

This report is based on my presentation at the Workshop on Computational Linguistics on East Asian
languages in 2022. Some examples from treebanks are from UD v2.10; please correct me if the data used are
outdated.

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Conclusion

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Turkic Languages

Figure: Distribution of the Turkic languages

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Conclusion

References

Turkic Languages and UD
Southwestern (Oghuz)• Turkish (Turkey; ~80 mil.)Northwestern (Kipchak)• Kazakh (Kazakhstan; ~18 mil.)• Tatar (Republic of Tatarstan, Russia; ~5 mil.)• Kyrgyz (Kyrgyzstan; ~4 mil.)Southeastern (Karluk)• Uyghur (Xinjiang, China; ~10 mil.)Northeastern (Siberian)• Sakha (Republic of Sakha, Russia; ~0.5 mil.)• Old Turkic (Current Mongolia; Extinct)
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References

Turkic treebanks in UD
Group

SW

SE
NW
NE

Language

TurkishTurkishGerman
UyghurKazakhKyrgyzTatar
Sakha(Yakut)Old Turkish(Old Turkic)

Treebank
Kenet (Kuzgun et al., 2022b)
Penn (Cesur et al., 2022)
Tourism (Kuzgun et al., 2022a)
Atis (Köse and Yıldız, 2022)
FrameNet (Marşan et al., 2021)
GB (Çöltekin, 2020)
IMST (Çöltekin et al., 2021)
BOUN (Türk et al., 2020)
PUD (Uszkoreit et al., 2021)
SAGT (Çetinoğlu and Çöltekin, 2022)

Latest
v2.10
v2.10
v2.10
v2.10
v2.9
v2.7
v2.11
v2.11
v2.12
v2.10

Tokens
178K
87K
92K
45K
19K
17K
57K
122K
16K
37K

Annotation
ManualManualManualSemi-auto
ManualManualSemi-auto
ManualSemi-auto
ManualSourceDictionary
Penn Treebank
Reviews
ATIS
FrameNet
Grammar book
IMST Treebank
Miscellaneous
PUD
SpokenUDT (Eli et al., 2016)
KTB (Makazhanov et al., 2015)
KTMU (Benli, 2023)
NMCTT (Taguchi et al., 2022)
YKTDT (Merzhevich and Gerardi, 2021)

v2.8
v2.10
v2.12
v2.11
v2.10

40K
10K
7K
1K
495

ManualManualManualManualManualBooks
Miscellaneous
News etc.
News
Miscellaneous

Tonqq (Derin and Harada, 2021)

v2.10

158

ManualInscriptions

Table: Details of the Turkic treebanks available as of UD v2.10. Semi-auto in the
Annotation column means that the annotation was done by combining an automatic
tagging process with manual annotation.

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Conclusion

References

UD Tatar NMCTT• The first and only treebank for Tatar• NMCTT: NAIST Multilingual Corpus Tatar (funded by Nara Instituteof Science and Technology)• Online news text (tatar.inform) with the condition that the source link to
the news page is shown• 148 sentences, 2280 tokens• Marks code-switching and its boundaries (will be incorporated to the
SAGT style)
ID FORMLEMMAUPOS FEATSHEAD DEPREL MISC
1 Татарстанда
ТатарстанPROPN Case=Loc|Number=Sing
5
obl
LangID=TT
2 коронавирустан коронавирус NOUN Case=Abl|Number=Sing4
nmod
CSPoint=коронавирус§тан|LangID=MIXED[TT§RU]
3 беренче
беренче
ADJ
_
4
amod
LangID=TT
4 прививканы
прививкаNOUN Case=Acc|Number=Sing5
obj
CSPoint=прививкас§ны|LangID=MIXED[TT§RU]
5 ясатыргаясаVERB VerbForm=Inf|Voice=Cau 0
root
LangID=TT
6 мөмкин
мөмкинAUX_
5
aux
LangID=TT|SpaceAfter=No
7 .
.
PUNCT _
5
punct LangID=OTHER

Table: An example of UD Tatar. The sentence is transcribed as Tatarstanda
koronavirustan berençe privivkanı yasatırğa mömkin.
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Code-switching annotation
Frequent code-switching with Russian: NMCTT marks the language code(s)and the code-switching boundary in the MISC column.
• LangID: Language ID (will be changed to CSID and lang from the next
version to be unified with SAGT)• CSPoint: Code-switching point. § marks the code-switching boundary.
• If LangID=MIXED, the segment-level LangIDs are shown in brackets.
• коронавирус§тан: LangID=MIXED[RU§TT] “from coronavirus”• гомум§техник: LangID=MIXED[TT§RU] “polytechnic”
ID FORMLEMMAUPOS FEATSHEAD DEPREL MISC
1 Татарстанда
ТатарстанPROPN Case=Loc|Number=Sing
5
obl
LangID=TT
2 коронавирустан коронавирус NOUN Case=Abl|Number=Sing4
nmod
CSPoint=коронавирус§тан|LangID=MIXED[TT§RU]
3 беренче
беренче
ADJ
_
4
amod
LangID=TT
4 прививканы
прививкаNOUN Case=Acc|Number=Sing5
obj
CSPoint=прививкас§ны|LangID=MIXED[TT§RU]
5 ясатыргаясаVERB VerbForm=Inf|Voice=Cau 0
root
LangID=TT
6 мөмкин
мөмкинAUX_
5
aux
LangID=TT|SpaceAfter=No
7 .
.
PUNCT _
5
punct LangID=OTHER

Table: An example of UD Tatar. The sentence is transcribed as Tatarstanda
koronavirustan berençe privivkanı yasatırğa mömkin.
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Issues in Turkic UD
Issues I faced during my annotation of Tatar UD

Tokenization• Locative adjectivizer -ki: separate token?
• Tokenization by word vs. by morpheme

Part-of-speech• Usage of particles PART• Converbs: VERB or ADV?
• Adjectivized locative nouns: ADJ or NOUN?

Morphology• Bare noun: Case=Nom|Number=Sing or nothing?
• Converb: VerbForm=Conv
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References

Tokenization: Turkic locative adjectivizer -ki-ki• Shared across many Turkic languages• Used for a locative noun to modify the next noun (1)• Recursion (2)• UD’s flat (non-nested) annotation of morphological features cannot
handle this(1) Turkish
Berlin-de-ki (kişi)Berlin-loc-ki person‘(The person) in Berlin’(2) [[Berlin-de-ki]-ler-de-ki]-ler-...
Berlin-loc-ki-pl-loc-ki-pl-...
‘... those that are at those in Berlin’s’
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Conclusion

References

Tokenization: Turkic locative adjectivizer -ki

Solutions

1. -ki as an independent token with the case relation (e.g., GB and SAGT; Table)
2. -ki as an independent token with the dep:der relation (ATIS)
3. Introduce hierarchical morphological annotation (cf. UniMorph 4.0 (Batsuren
et al., 2022))

In UD-Tatar NMCTT-ki is not tokenized separately (also in Kyrgyz KTMU)• This still does not solve the nested features(Turkish ev-ler-de-ki-ler-de-... or Tatar öy-lär-dä-ge-lär-dä-...)• Any suggestions?
ID
1-2
1
2

FORM
Berlin’deki
Berlin’de
ki

LEMMA
_
Berlin
ki

UPOS
_
PROPN
ADP

FEAT
_
Case=Loc_

DEPREL
nmod
case

Table: Tokenization and tags of -ki as a separate token.

ID
1

FORM
Берлиндагы

LEMMA
Берлин

UPOS
PROPN

FEAT
Case=Loc

DEPREL
amod

Table: Tokenization and tags of -ki as morphologically suffixed to the stem.
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Conclusion

References

Tokenization: word vs. morpheme

Word boundary in orthographies• Modern Turkic languages: syntactic word boundaries are split by spacesin the orthography (+ some exceptions)• Old Turkic: word boundaries are not necessarily split in the original
Old Turkic inscription text
Inscription:
Transcription
Reconstruction1 :𐰃𐰡𐰆𐰉𐰄𐰇𐰘𐰃𐱅𐰘
j2 t2 i j2 ü z b1 o lt i
jeti jüz boltï

1 Reconstruction by the Language Committee of Ministry of Culture and Information of the Republic of Kazakhstan

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References

Tokenization: word vs. morpheme
Tokenization in the Old Turkic Tonqq Treebank• Old Turkic Tonqq treebank tokenizes every morpheme.
(3) 𐰃𐰡𐰆𐰉𐰄𐰇𐰘𐰃𐱅𐰘
jeti
jüz
bol-tï
seven hundred be-pst‘(They were) seven hundred’
FORM

LEMMA

UPOS

FEAT

𐰃𐱅𐰘
𐰄𐰇𐰘
𐰞𐰆𐰉
𐰃𐱃

_
_
_
_

NUM
NUM
VERB
AUX

_
_
_
_

Table: Tonqq-style tokenization of (3).

FORM

lemma

UPOS

FEAT

𐰃𐱅𐰘
𐰄𐰇𐰘
𐰃𐰡𐰆𐰉

𐰃𐱅𐰘
𐰄𐰇𐰘
𐰞𐰆𐰉

NUM
NUM
VERB

_
_
Tense=Past

Table: Conventional tokenization of (3).

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Conclusion

References

Tokenization: word vs. morpheme
Which is suitable in UD?
• Controversial in linguistics• This study’s position: word-splitting tokenization

Why not morpheme-splitting tokenization• Inconsistent: Other Turkic languages in UD do not split by morphemes• Ambiguous: The difference between independent words and boundmorphemes is less clear• Less informative: The current morpheme-split method does not tell us
anything about morphological features

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Conclusion

References

Part-of-speech: Particle PARTIn general, the PART tag should be used restrictively and only whenno other tag is possible. — UD Guideline

Use of PART in Turkic UD• Not unified, as in the Table• UD Turkish’s guideline defines that only değil negating non-predicate
word is PART• Actual usage varies in every treebank
Treebank

PART words

BOUN
SAGT
UDT
KTB
KTMU
NMCTT

ki (that), çok (much), and other 61 wordsdeğil and other 7 German words
de (also), qëni (well), belkim (maybe), epsus (pity), and other 18 words
ma (yes-no question particle), šïGar (probably), and other 7 words
None
None

Table: Usage of PART and their PART words. Uyghur and Kazakh words are transliterated for convenience.
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References

Part-of-speech: Particle PARTIn general, the PART tag should be used restrictively and only whenno other tag is possible. — UD Guideline

Solution• The status of these closed-class POS categories is controversial in
linguistics• For UD, having a unified policy is better than being inconsistent• Following the guideline, try not to use PART• Instead, use AUX, ADV, or other feasible tags

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Conclusion

References

Part-of-speech: Converb
Converb• Verb form modifying other predicates adverbially (Haspelmath, 1995)• Also called “adverbial participle”• Disagreement: VERB or ADV?
Treebank

UPOS

FEAT

Kenet
Penn
Tourism
Atis
GB
FrameNet
BOUN
PUD
IMST
SAGT
KTB
KTMU
NMCTT
UDT
YKTDT

ADV
ADV
ADV
ADV
VERB
ADV
VERB
ADV
VERB
VERB
VERB
VERB
VERB
VERB
NA

_
_
_
_
VerbForm=Conv___
VerbForm=Conv
VerbForm=Conv
VerbForm=Conv
VerbForm=Conv
VerbForm=Conv
VerbForm=Conv
NA

Table: UPOS and FEAT annotation for converbs. An underscore means no annotation given to the form in the
corpus; NA means converb is unattested in the corpus.

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Introduction

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Conclusion

References

Part-of-speech: Converb
Issue• VERB or ADV?

Solution• Converbs (at least in Turkic) are VERB
• Turkic converbs are productively inflected• In UD Tatar, the four converb forms are distinguished in FEATS• -Ip: VerbForm=Conv• -GAnçI: Aspect=Imp|VerbForm=Conv• -A: Aspect=Prog|VerbForm=Conv• -GAç: Aspect=Perf|VerbForm=Conv• Remaining issue: Aspect conflict in grammaticalized constructions• Tatar: jaz-ğal-ıy başla-dı “S/he started to write many times”• Aspect=Iter (-GAlA) and Aspect=Prog (-A)?
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Conclusion

References

Part-of-speech: Adjectivized locative noun
-ki again: NOUN or ADJ?
• Generally, -ki with locative is productively derived from noun
• Therefore, it should be tagged as NOUN (or PROPN)
Treebank

UPOS

FEAT

Kenet
Penn
Tourism
Atis
GB
FrameNet
BOUN
PUD
IMST
SAGT
KTB
KTMU
NMCTT
UDT
YKTDT

ADJ
ADJ
ADJ
ADJ
NOUN + ADP
NOUN + ADP
NOUNNOUN + ADP
NOUN + ADP
NOUN + ADP
NOUN
NOUN
NOUN
NOUN
NOUN

amod
amod
nmod
amod
nmod
amod
amod
amod
nmod
nmod
amod
nmod:poss, nmod
amod
amod
nmod

Table: UPOS and FEAT annotation for -ki.
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Conclusion

References

Morphology: Bare noun
Default unmarked noun form
• Nominative Case=Nom• Singular Number=Sing• Agrees with verbs in 3rd person Person=3• Differences across Turkic treebanks
Language

TurkishTurkish-German
UyghurKazakhKyrgyzTatar
Yakut
Old Turkic

Treebank

Case=Nom

Number=Sing

Person=3

Kenet
Penn
Tourism
Atis
GB
FrameNet
BOUN
PUD
IMST
SAGT
UDT
KTB
KTMU
NMCTT
YKTDT
Tonqq

Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
N

Y
Y
Y
Y
Y
Y
Y
N
Y
Y
N
N
Y
Y
N
N

Y
Y
Y
Y
N
Y
Y
Y
Y
N
N
N
Y
N
N
N

Table: Comparison of annotation for a bare noun.
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Introduction

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Conclusion

References

Morphology: Bare noun

Solution• Case (nominative) and number (singular) are changeable features of thenominal paradigm• Person is not a distinctive feature of the NOUN paradigm (NOUN is always
Person=3)• Bare nouns should be marked as Case=Noun|Number=Sing

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Introduction

Issues and Solutions

Conclusion

References

Morphology: Converb
Issue

Many of the Turkish treebanks do not tag converb forms as VerbForm=Conv

Solution

Converbs should be tagged as VerbForm=Conv
Treebank

UPOS

FEAT

Kenet
Penn
Tourism
Atis
GB
FrameNet
BOUN
PUD
IMST
SAGT
KTB
KTMU
NMCTT
UDT
YKTDT

ADV
ADV
ADV
ADV
VERB
ADV
VERB
ADV
VERB
VERB
VERB
VERB
VERB
VERB
NA

_
_
_
_
VerbForm=Conv___
VerbForm=Conv
VerbForm=Conv
VerbForm=Conv
VerbForm=Conv
VerbForm=Conv
VerbForm=Conv
NA

Table: UPOS and FEAT annotation for converbs (-Ip, -ArAk, etc.). An underscore means no annotation given
to the form in the corpus; NA means converb is unattested in the corpus.

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Introduction

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Conclusion

References

Concluding Remarks
This study ...
• Introduced UD-Tatar NMCTT• Showed disagreeing annotation of Turkic UD treebanks• Tokenization• POS tags
• Morphological features• Proposed a solution for each caseFor more universal Universal Dependencies ...
• Cross-lingual and cross-treebank discussions• Involvement of linguists

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Introduction

Issues and Solutions

Conclusion

References

Thank you!

Contact: ctaguchi@nd.edu
Website: https://ctaguchi.github.io

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Introduction

Issues and Solutions

Conclusion

References

References I
Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa, Nizar Habash, Witold KieraÅ›, GÃ¡bor Bella, Brian
Leonard, Garrett Nicolai, Kyle Gorman, Yustinus Ghanggo Ate, Maria Ryskina, Sabrina Mielke, Elena
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Coler, Jaime Rafael Montoya Samame, Delio Siticonatzi Camaiteri, EsaÃº Zumaeta Rojas, Didier LÃ³pez
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Adam Ek, David Guriel, Peter Dirix, Jean-Philippe Bernardy, Andrey Scherbakov, Aziyana Bayyr-ool,
Antonios Anastasopoulos, Roberto Zariquiey, Karina Sheifer, Sofya Ganieva, Hilaria Cruz, RitvÃ¡nKarahÃ³Ç§a, Stella Markantonatou, George Pavlidis, Matvey Plugaryov, Elena Klyachko, Ali Salehi,
Candy Angulo, Jatayu Baxi, Andrew Krizhanovsky, Natalia Krizhanovskaya, Elizabeth Salesky, Clara
Vania, Sardana Ivanova, Jennifer White, Rowan Hall Maudslay, Josef Valvoda, Ran Zmigrod, Paula
Czarnowska, Irene Nikkarinen, Aelita Salchak, brijesh bhatt, Christopher Straughn, Zoey Liu,
Jonathan North Washington, Yuval Pinter, Duygu Ataman, Marcin Wolinski, Totok Suhardijanto, Anna
Yablonskaya, Niklas Stoehr, Hossep Dolatian, Zahroh Nuriah, Shyam Ratan, Francis M. Tyers,
Edoardo M. Ponti, Grant Aiton, Aryaman Arora, Richard J. Hatcher, Ritesh Kumar, Jeremiah Young,
Daria Rodionova, Anastasia Yemelina, Taras Andrushko, Igor Marchenko, Polina Mashkovtseva,
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Chodroff, Mans Hulden, Miikka Silfverberg, Arya D. McCarthy, David Yarowsky, Ryan Cotterell, Reut
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Ibrahim Benli. UD kyrgyz KTMU.
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https://github.com/UniversalDependencies/UD_Turkish-Penn, 2022.
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Mehmet Oguz Derin and Takahiro Harada. Universal Dependencies for Old Turkish. In Proceedings of theFifth Workshop on Universal Dependencies (UDW, SyntaxFest 2021), pages 129–141, Sofia, Bulgaria,
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Aslı Kuzgun, Neslihan Cesur, Olcay Taner Yıldız, Oğuzhan Kuyrukçu, Büşra Marşan, Bilge Nas Arıcan,Neslihan Kara, Deniz Baran Aslan, Ezgi Sanıyar, and Cengiz Asmazoğlu. UD Turkish Tourism.
https://github.com/UniversalDependencies/UD_Turkish-Tourism, 2022a.
Aslı Kuzgun, Neslihan Cesur, Olcay Taner Yıldız, Oğuzhan Kuyrukçu, Arife Betül Yenice, Bilge Nas Arıcan,and Ezgi Sanıyar. UD Turkish Kenet.
https://github.com/UniversalDependencies/UD_Turkish-Kenet, 2022b.
Mehmet Köse and Olcay Taner Yıldız. UD Turkish Atis.
https://github.com/UniversalDependencies/UD_Turkish-Atis, 2022.
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References

References IIIBüşra Marşan, Neslihan Kara, Merve Özçelik, Bilge Nas Arıcan, Neslihan Cesur, Aslı Kuzgun, Ezgi Sanıyar,Oğuzhan Kuyrukçu, and Olcay Taner Yildiz. Building the Turkish FrameNet. In Proceedings of the 11th
Global Wordnet Conference, pages 118–125, University of South Africa (UNISA), January 2021. Global
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Tatiana Merzhevich and Fabrício Ferraz Gerardi. UD Yakut YKTDT.
https://github.com/UniversalDependencies/UD_Yakut-YKTDT, 2021.
Chihiro Taguchi, Sei Iwata, and Taro Watanabe. Universal Dependencies Treebank for Tatar: Incorporating
intra-word code-switching Information. In Proceedings of the Workshop on Resources and Technologies
for Indigenous, Endangered and Lesser-resourced Languages in Eurasia (EURALI), Marseille, France,
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Utku Türk, Furkan Atmaca, �Saziye Betül Özateş, Gözde Berk, Seyyit Talha Bedir, Abdullatif Köksal,
Balkız Öztürk Ba �saran, Tunga Güngör, and Arzucan Özgür. Resources for Turkish Dependency Parsing:
Introducing the BOUN Treebank and the BoAT Annotation Tool, 2020.
Hans Uszkoreit, Vivien Macketanz, Aljoscha Burchardt, Kim Harris, Katrin Marheinecke, Slav Petrov, Tolga
Kayadelen, Mohammed Attia, Ali Elkahky, Zhuoran Yu, Emily Pitler, Saran Lertpradit, Savas Cetin,
Martin Popel, Daniel Zeman, Francis Tyers, Çağrı Çöltekin, Utku Türk, Furkan Atmaca, Şaziye BetülÖzateş, Abdullatif Köksal, Balkız Öztürk Başaran, Tunga Güngör, and Arzucan Özgür. UD Turkish PUD.
https://github.com/UniversalDependencies/UD_Turkish-PUD, 2021.
Özlem Çetinoğlu and Çağrı Çöltekin. Two languages, one treebank: building a Turkish–German
code-switching treebank and its challenges. Language Resources and Evaluation, pages 1–35, 2022. ISSN
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Çağrı Çöltekin. UD Turkish GB. https://github.com/UniversalDependencies/UD_Turkish-GB,
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Conclusion

References

References IVÇağrı Çöltekin, Gülşen Cebiroğlu Eryiğit, Memduh Gökırmak, Hüner Kaşıkara, Umut Sulubacak, andFrancis Tyers. UD Turkish IMST.
https://github.com/UniversalDependencies/UD_Turkish-IMST, 2021.

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