The Leeds Arabic Discourse Treebank: Annotating Discourse Connectives forArabic

Amal Al-Saif, Katja Markert

School of ComputingUniversity of Leeds, Leeds, UK, LS2 9JT

assaif@comp.leeds.ac.uk, markert@comp.leeds.ac.uk

AbstractWe present the first effort towards producing an Arabic Discourse Treebank, a news corpus where all discourse connectivesare identified and annotated with the discourse relations they convey as well as with the two arguments they relate. Wediscuss our collection of Arabic discourse connectives as well as principles for identifying and annotating them in context,taking into account properties specific to Arabic. In particular, we deal with the fact that Arabic has a rich morphology:we therefore include clitics as connectives as well as a wide range of nominalizations as potential arguments. We presenta dedicated discourse annotation tool for Arabic and a large-scale annotation study. We show that both the human iden-tification of discourse connectives and the determination of the discourse relations they convey is reliable. Our currentannotated corpus encompasses a final 5651 annotated discourse connectives in 537 news texts. In future, we will releasethe annotated corpus to other researchers and use it for training and testing automated methods for discourse connectiveand relation recognition.

1. IntroductionDiscourse relations such as CAUSAL or CONTRAST

relations between textual units play an important rolein producing a coherent discourse. They are widelystudied in theoretical linguistics (Halliday and Hasan,1976; Hobbs, 1985), where also different relation tax-onomies have been derived (Hobbs, 1985; Knott andSanders, 1998; Mann and Thompson, 1988; Marcu,2000). Discourse relations can be signalled by ex-plicit lexical indicators, so-called discourse connec-tives (Marcu, 2000; Webber et al., 1999; Prasad et al.,2008a). We follow (Prasad et al., 2008a) in definingdiscourse connectives as lexical expressions that relatetwo text segments that express abstract entities suchas events, belief, facts or propositions. These text seg-ments are called the arguments of the discourse con-nective. In Ex. 1 the connective because indicatesa CAUSAL relation between Jack not getting a highmark and his fatigue at exam time. In Ex. 2, the con-nective however indicates a CONTRAST relation. Weindicate discourse connectives and the two argumentsvia annotated square brackets.

(1) [Because]DC [he was very tired during theexam,]Arg2 [Jack did not achieve a highmark.]Arg1

(2) [The TV was broken.]Arg1[However]DC,[I wasable to fix it]Arg2

Discourse connectives are often used as an importantfeature in the automatic recognition of discourse rela-

tions, a task useful for many applications such as au-tomatic summarization, question answering and textgeneration (Hovy, 1993; Marcu, 2000). Recently, toenable corpus studies and automatic discourse relationrecognition algorithms, the Penn Discourse Treebank(PDTB) has been developed (Prasad et al., 2008a) –an English corpus which is annotated for discourseconnectives, the relations they convey, which they callsenses, and their arguments.1 One of its main attrac-tions is that its annotation is theory-neutral (for ex-ample, it does not subscribe to any restrictions on thedistance of the two arguments of a connective). It hasalso been shown to be extensible to other languagessuch as Hindi (Prasad et al., 2008b), Turkish (Zeyrekand Webber, 2008) and Chinese (Xue, 2005).We extend these efforts to Modern Standard Ara-bic (MSA) by producing the Leeds Arabic DiscourseTreebank (LADTB). The remainder of this paper is or-ganized as follows: Section 2. describes related work.Section 3. describes our methodology for collectingthe potential discourse connectives in MSA. A briefdescription of the annotation scheme follows in Sec-tion 4. The corpus, annotation tool, and the annotationmethodology are discussed in Section 5. The resultsof our agreement studies and the gold standard corpus

1The PDTB project has been extended to also annotateimplicit discourse relations, i.e. discourse relations whichare not indicated via discourse connectives. In this firststudy for Arabic, we focus on discourse relations signaledexplicitly via connectives.

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details are in Sections 6. and 7., respectively.

2. Related WorkSeveral textual corpora of Arabic exist. Some of themare available with Part-of-Speech and syntactic anno-tation such as the Arabic Treebank (ATB) (Maamouriand Bies, 2004). The Prague Arabic DependencyTreebank (PADT), which is smaller in scale than theATB, contains multilevel annotations, including mor-phological and analytical level of linguistic represen-tation (Hajic et al., 2004). Moreover, a recent effort byDukes and Habash (2010) has produced The QuranicArabic Corpus, a free annotated linguistic resourcewhich provides morphological annotation and syntac-tic analysis (using dependency grammar) of the HolyQuran.Surprisingly, the annotation level of existing Arabiccorpora has not yet included the discourse layer. Al-Sanie et al. (2005) and Seif et al. (2005) discuss alimited set of rhetorical relations and discourse con-nectives. However, they did not distinguish betweendiscourse connectives such as

à B /l↩an/because2 and

other syntactic connectors such as prepositions likeú

¯ /fy/in or ©Ó /m↪/with, where the latter signal a se-

mantic relation between two concrete objects insteadof a discourse relation between abstract entities suchas clauses or sentences. Moreover, the studies had asmall empirical basis using only a small number ofArabic texts and no agreement studies on identifica-tion of discourse connectives and relations in contexthave been carried out. Therefore, our work is the firstprincipled discourse annotation effort for Arabic.We work on the syntactically annotated Arabic PennTreebank v.2 (Maamouri and Bies, 2004), which weextend to a discourse-level resource by identifyingits explicit discourse connectives and annotating themwith the discourse relations they convey as well astheir arguments. We based our annotation guidelineson the same principles as the PDTB but adapt andexpand the annotation to take into account propertiesspecific to Arabic.

3. Collecting Arabic ConnectivesAlthough several references in the Arabic literature(Al-Warraki and Hasanayn, 1994; Ryding, 2005;Alansari, 1985; Alfarabi, 1990) point out the discourseusage of connectives such as

à B /l↩an/because and

áºË /lkn/but, no single exhaustive list of Arabic dis-course connectives exist.

2Arabic examples contain in order: the Arabic right-to-left script, the transliteration (standards ISO/R 233 and DIN31635) and the English translation (if possible).

We collected a large set of Arabic discourse con-nectives using text analysis and corpus-based tech-niques. We enhanced the ones mentioned in the litera-ture with manual extraction of all connectives from 50randomly selected texts from the Penn Arabic Tree-bank and from 10 different web sites. In addition,we extracted all lexical items with connective-typicalPOS tags (such as conjunctions) automatically fromthe Penn Arabic Treebank (Al-Saif et al., 2009). Theresulting list was manually verified by two Arabic na-tive speakers.Our final list contains 91 basic Arabic discourse con-nectives, enhanced with 16 modified forms of basicconnectives (such as @

X @ ú

�æk /h. ta ad

¯a/even if as a

modified form of @X @/ad

¯a/ if), yielding 107 discourse

connectives overall. This number is comparable tothe number of 100 distinct English connectives in thePDTB. Tabel 4 shows the most frequent connectivesin the LADTB.

4. Annotation SchemeWe followed the annotation principles in the PDTB asfar as possible. Necessary adaptations were made totake into account properties specific to Arabic. PDTBannotation is based on lexicalized grammar theory.The anchor of the annotation is the lexical item - adiscourse connective (DC). The argument labels ofthe signalled relation are partially syntactically driven,in that the Arg2 label is assigned to the argumentwith which the connective was syntactically associ-ated. The Arg1 label, however, can refer to an abstractobject at any distance from the connective.

4.1. Types of Discourse ConnectivesDiscourse connectives in the PDTB are coordinatingor subordinating conjunctions such as and, but andor, adverbials such as then, later and otherwise, andprepositional phrases such as in contrast and as a re-sult. All these are also used for MSA (see Examples3, 4 and 5).

(3) [ áÒ�JË @

�é

¢ëAK. ] DC[Aî

DºË] Arg1[. ' @Yg. èPñ¢

�JÓ

�èPAJ�Ë@]

Arg2

[al-syarh mtt.wrh gdan.]Arg1[lknha]DC[bahz. ah al-t¯mn]Arg2

[The car is so modern.]Arg1 [but]DC [it is tooexpensive]Arg2

(4) ZAÖÞ� ú

¯ PQÒ

�J�AK.

��Êm�

�' �

IKA¿

�H@Q

KA¢Ë@] DC1[

à@ Ñ

«P]

Arg2[Q�K A�J�K ÕË

�éJ

KYÖÏ @

�èAJm

Ì'@] DC2[à@ B@] , Arg1[

�éJKYÖÏ @

[rgm an]DC1 [al-t.a↩irat kant th. lq bastmrar fy sma↩al-madynh ]Arg1, [ala ↩an]DC2 [al-h. ayah al-mdnyh lm

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tt↩at¯r.]Arg2

[Although]DC[the planes were flying continuously inthe city sky]Arg2[ civilian life was not affected]Arg1

(5) . AJ.ª�JÓ

àA¿ Y

�®Ë Arg1[. É

®mÌ'@ Pñ

�k áÓ áºÒ

�JK ÕË YÔg@ ]

Arg2[ù®

��

���ÖÏ @ úÍ@ I. ë

X] DC[, ÉK. A

�®ÖÏ @ ú

¯]

[ah. md lm ytmkn mn h. d. wr al-h. fl.]Arg1 lqd kan mt↪ba.[fy al-mqabl,]DC [d

¯hb ala ’l-mstsfa]Arg2

[Ahmed was unable to attend the ceremony.]Arg1He was tired. [In contrast]DC [he went to thehospital.]Arg2

However, our analysis shows that, in addition, manytypical discourse relations are expressed in Arabic viaprepositions where normally one argument of the con-nective is a nominalization (Al-Mazdar).3 Thus, inEx. 6

©JÊJ.�K/tblyg/informing is the Al-Mazdar form of

©ÊK. /blg/inform. Interestingly, prepositions are not con-sidered as discourse connectives in the English PDTB.In addition, what is Al-Mazdar in Arabic is not neces-sarily a nominalization in English. For example, theequivalent of agriculture is Al-Mazdar form in Arabic,namely ¨ P P/z r ↪. However, it is not a nominaliza-tion in English.

(6) à@Y

�®

¯ á«

©JÊJ.

�JË]DC[È] Arg1[

�é£Qå

��Ë @ Q»QÓ úÍ@ A

JJ.ë

X]

Arg2[�éJÖÞ

�QË @�é»Qå

��Ë @

��

KA

�Kð

[d¯

hbna ’la mrkz al-srt.t.]Arg1[l]DC[ltblyg ↪n fqdanwt¯a↩iq alsrkh alrsmyh]Arg2

[We went to the police station]Arg1 [for]DC [in-forming about the loss of the company’s officialdocuments.]Arg2

Similar to Turkish and Hindi, but different from En-glish, not all connectives are white-space separated(sequences of) tokens; instead, clitics such as È

/l/for/of (see Ex. 6), H. /b/by and

¬ /f/then are alsopossible. Such strings are often ambiguous betweenbeing a discourse connective and just a letter sequencewithin a word such as

¬ /f/then (if a discourse con-

nective) in �èA

�J¯ /ftah /girl.

4.2. Argument TypesWe consider any text segments expressing abstract ob-jects as arguments. For Arabic, these might be one ormore, tensed or untensed, verbal sentences or clausesgmlh f↪lyh, noun sentences gmlh ↩smyh, anaphoric ex-pressions (if they refer to an abstract object such asmany demonstrative pronouns) or verb ellipses.

3Al-Mazdar is a well defined noun category in the Ara-bic literature with 58 noun forms.

Figure 1: Discourse relations in the LADTB.

The main difference to English is the inclusion of cer-tain noun sentences. The Arabic noun sentence isequivalent to one of two English sentences/clauses: (i)a verbal phrase of the form (x verb-to-be y) (such asthe university is famous/ �

èPñîD��Ó

�éªÓAm.

Ì'@) or (ii) a nounphrase (such as famous university/ �

èPñîD��Ó

�éªÓAg. ).

The latter is normally not an abstract object, exceptif it is a nominalization. We allow the first type andnominalizations (Al-Mazdar) from the second type asarguments of a discourse connective.

4.3. Types of Relations

We use the same 4 main relation classes as thePDTB does for English: TEMPORAL, CONTIN-GENCY, COMPARISON and EXPANSION. However,we reduce the number of subclass relations we useto 18. We especially do not currently annotate fur-ther fine-grained distinctions, such as whether a con-ditional is counterfactual, as done in the PDTB. Futureversions of the LADTB might include finer-graineddistinctions. Figure 1 shows the hierarchy of discourserelations for Arabic.We introduce two new relations at subclass level as wefound them necessary in our pilot annotation for Ara-bic. These are EXPANSION.Background and COM-PARISON.Similarity.

EXPANSION.Background applies when the argu-ment that is syntactically associated with the con-nective describes prior eventualities which are back-ground information of the other argument. This wasfrequent in news reports (see Ex. 7).

(7) ÈAÒ�

�Ë@ Èñ¢�@ Õæ�AK.�

HYj�JÓ á« �A

�KQ

��K @

�éËA¿ð

�IÊ

�®

K

2048

YªK.

�@YJ.�� Õ

�¯A¢Ë@ ZCg. @

à@]

�é�@ñ

ªË@ éJË @ ù

Ò�J��K ø

YË@

Y�¯ ]DC[ð ] Arg1[

�éKñm.

Ì'@ È@ñkB@ á�m��' Y»

A�K @

X @ Qê

¢Ë@

ø

@ ZYK.àðX �

��A

KQK. Qm�'

. AëYîD��� ú

�æË @

�é

®�AªË@

�IËAg

Arg2[.àB@ ú

�æk

XA

�®

K @

�éJÊÔ

«

nqlt wkalh aytrtas ↪n mth. dt¯

basm ast.wl alsmal ald¯

ytntmy alyh algwas. h [an agla↩ alt.aqm sybda b↪d alz. hrad¯

a ta↩kd th. sn alah. wal algwyh ]Arg1[w]DC[ qd h. altal↪as. fh alty yshdha bh. r barnats dwn bd↩ ay ↪mlyhanqad

¯h. ta ’lan. ]Arg2

ITAR - The TASS spokesman for the NorthernFleet, which the submarine belongs to, said [that theevacuation of the crew will begin this afternoon ifweather conditions improve. ]Arg1 [(And)]DC [thestorm in the Barents Sea had prevented any rescueoperation so far.]Arg2

COMPARISON.Similarity applies when the connec-tive indicates that the two arguments express similarabstract objects. It is therefore a complement to thecontrast relation.

(8) �Iëñ

�� Õç

�' �

@QË @ ú

¯

�é�A�QK. C

�J�¯

àAKQº�ªË@

à@]

�HAJÊÔ

« ú

¯ AJ. Ë A

« É�m�'

]DC[AÒ»] Arg1[AÒî�D�Jk.

Arg2[.�éjÊ�ÖÏ @

�H@ñ

�®Ë@ YK úΫ

­¢

mÌ'@

[an al↩skryyn qtla brs. as. h fy alras t¯m swht gt

¯thma-

] Arg1 [kma]DC [ yh. s. l galba fy ↪mlyat alh˘

t.f ↪la ydalqwat almslh. t. ] Arg2[The military were killed by a bullet in the headand their bodies disfigured]Arg1[as]DC [often hap-pens in abductions by armed groups]Arg2

5. Agreement Studies5.1. The CorpusWe base our study on the Penn Arabic Treebank (Part1 v. 2.0) as part of the largest syntactically annotatedcorpus for Arabic. It consists of 734 files containingroughly 166K words of written Modern Standard Ara-bic newswire from the Agence France Press.

5.2. Arabic Discourse Annotation Tool (ADA)and Annotation Process

We developed a dedicated discourse annotation toolto deal with requirements specific to Arabic discourseannotation such as the annotation of clitics and right-to-left script order. The tool allows selection of Arabicor English annotation (see Figure 2).It also highlights all potential discourse connectivesfrom our connectives list (see Section 3.), includingpotential clitics. This is also shown in Figure 2. Theannotator reads the text to get an overall understand-ing, and then makes a series of decisions for each po-tential connective in context.

Figure 2: Discourse Annotation Tool for Ara-bic/English: screenshots before annotation

Figure 3: Discourse Annotation Tool for Ara-bic/English: screenshot after annotation.

1. If the potential connective is in this particularcontext not a connective (for example, becauseit does not relate two abstract entities), highlight-ing is removed and all annotation ceases.

2. If the potential discourse connective is indeedused as a connective, annotators will mark thetext segments that express the two arguments of

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the connective as well the discourse relation itconveys from a drop-down list of relations. Sim-ilar to the English annotation, annotators are al-lowed to use more than one relation, if a con-nective is deemed to express two relations at thesame time. The screenshot in Figure 3 shows anexample annotation.

3. Annotators are allowed to add comments into acomment box.

5.3. Annotation MethodologyAnnotation was conducted by two independent nativespeakers of Arabic who were not involved in tool orscheme development. Agreement is measured on twotasks. The first task TASK I measures whether anno-tators agree on the binary decision on whether an itemconstitutes a discourse connective in context (Step 1in the annotation procedure described above). Dueto clitics and Arabic’s complex morphology this taskis potentially harder than in English. Agreement ismeasured by the kappa statistic (Siegel and Castellan,1956). The second task TASK 2 measures whether an-notators agree on which discourse relation an identi-fied connective expresses. As annotators can use setsof relations for a connective, we use kappa as well avariant of kappa called alpha, which allows us to mea-sure partial agreement on sets while keeping kappa’sadvantage of factoring out random agreement (Art-stein and Poesio, 2008). A pilot annotation on 121texts was used to train the annotators and to clarify theannotation guidelines, if necessary. The actual anno-tation after training has been conducted on 537 texts.

6. ResultsAgreement on TASK I is highly reliable (N= 23331,percentage agreement of 0.95, kappa of 0.88). Fullagreement is shown in Table 1. Due to proliferationof ambiguous clitics, most potential connective tokensare actually not connectives so that only 5586 of a po-tential 23331 connectives are actually really discourseconnectives.Agreement on TASK II (relation assignment) is rela-tively low (N = 5586, percentage agreement of 0.66,kappa of 0.57, and alpha of 0.58). It turns out that oneof the major sources of disagreement is due to a con-vention in Arabic newswire writing: each sentence (ifnot introduced by an alternative connective) is intro-duced by ð /w/and, mostly without a specific discourserelation conveyed. This caused a high level of confu-sion. We therefore report agreement on three differentdatasets (see Table 2): the set of all identified con-nectives, the set of identified connectives excluding ð

/w/and and the set of identified connectives excludingð /w/and at the beginning of a paragraph (BOP). Wesee that reliability for connectives excluding rhetoricaluse of ð /w/and is good.Connectives are mostly unambiguous in English(Pitler et al., 2008). However, for Arabic we encoun-tered higher levels of ambiguity. The most ambigu-ous connectives at class level are in order ð /w/and,

¬

/f/then, AÒJ¯ /fyma/while, AÒ» /kma/as and á�g ú

¯ /fy

h. yn/while/in the same time. The most ambiguous con-nectives at sub-class level are again ð /w/and, then inorder H. /b/due to/because,

¬ /f/then and È /l/for/due

to. This also highlights the value of this study of con-nectives in context as we discovered several context-dependent usages of discourse connectives that werenot discussed in previous work on discourse connec-tives for Arabic (Al-Warraki and Hasanayn, 1994; Ry-ding, 2005; Alansari, 1985; Alfarabi, 1990). For ex-ample, ð /w/and is normally just associated with Con-junction in the literature but we discovered variousother relations it expresses.

Table 1: Inter-annotator reliability for discourse con-nective identification (TASK I)

All potential connectives (23331)Observed agreement 0.95Kappa 0.88Potential connectives w/o ð /w/and (15602)Observed agreement 0.95Kappa 0.82Potential connectives w/o ð /w/and at BOP (21200)Observed agreement 0.95Kappa 0.84

Table 2: Inter-annotator reliability for discourse rela-tions (TASK II)

All connectives (5586)Observed agreement 0.66Kappa of relations 0.57Alpha of relations 0.58Connectives excluding ð /w/and (1886)Observed agreement 0.80Kappa 0.77Alpha 0.80Connectives excluding ð /w/and at BOP (3500)Observed agreement 0.74Kappa 0.69Alpha 0.71

7. Gold StandardWe are now in the process of reconciling the anno-tations into a gold standard. First, we realized that

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ð /w/and at BOP is the most ambiguous connectiveand that due to its mostly rhetorical use, the anno-tators could not agree on its discourse use in con-text. Therefore, we for now assign automatically Ex-pansion.Conjunction to all disagreed instances of ð

/w/and at BOP.4 A further disambiguation study isnecessary for ð /w/and at BOP. Other automatic cor-rections of easily detectable annotation errors havealso taken place (such as making sure that modifiedforms of a connective were indeed only annotated asone and not as two connectives). In a second step, wenow reconcile other disagreements via further discus-sions and an arbitrator.The final LADTB contains 5651 annotated connec-tives, their relations and arguments in 537 files (75%of ATB, part 1). Table 3 summarizes the statistics ofthe LADTB corpus and the most and least frequentconnectives and relations. Of the potential 107 con-nective types we collected (see Section 3.), only 68occurred in the LADTB. Apart from the 18 single dis-course relations, 22 different set combinations of dis-course relations were also used. Also note that dueto automatic corrections, the number of all potentialconnectives as well as of real connectives in Table 3varies slightly from the number of connectives citedin the annotation study.

8. Conclusion and Future WorkWe present the first annotation study for discourse re-lations in Arabic, concentrating on explicit discourseconnectives. We show that identification of connec-tives is highly reliable and annotation of the discourserelations the connectives convey is reliable, if we ex-clude the purely rhetoric occurrence of the connec-tive ð /w/and at the beginning of paragraphs. In fu-ture, we aim to (i) measure the reliability of argumentassignment, (ii) release the agreed gold standard ofthe LADTB (Version I) and (iii) develop automaticmodels for connective recognition and relation disam-biguation.

AcknowledgmentsAmal Al-Saif is supported by a PhD scholarship from theImam Muhammad Ibn Saud University, Saudi Arabia. Wethank the British Academy for additional funding for theannotation study via Grant SG51944. We would also liketo acknowledge the contributions of the annotators LatifaAlsulaiti and Abdul-baqi Sharif in the actual annotation andBasmah Al-Soli, Boshra Al-shyban and Maryam Al-Gawiin the pilot annotation. A special thank you goes to Dr.Hussein Abdul-Raof for linguistic advice on the collection

4Note that other instances of ð /w/and are not treatedthis way.

of discourse connectives as well as to Bonnie Webber andother members of the PDTB team for useful discussions.

9. ReferencesAmal Al-Saif, Katja Markert, and Hussein Abdul-

Raof. 2009. Corpus-Based Study: Extensive Col-lection of Discourse Connectives For Arabic. InProceedings of The Saudi International Conference2009 (SIC09), Surrey, UK.

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Number of files 537Connective types 68Discourse relation types 18 plus 22 combinationsPotential connective tokens 23147Real discourse connectives 5651Most frequent connective ð /w/and (3826)Least frequent connectives I.

�®« /↪qb/after (noun) (2)

úÍ@�é¯A

�BAK. /balad. afh ala/in addition to (1)

ÉK. A�®ÖÏ AK. /balmqabl/in contrast (1)

Ñ«QK. /brgm/although (1)

É

�®K. /bfd. l/thanks to(1)

Q

k@ ú

æªÖß. /bm↪na ah˘

r/in other words(1)AÒÊ¿ /klma/as(1)½Ë

YË /ld

¯lk/for that(1)

Most frequent relations EXPANSION.Conjunction (2681)CONTINGENCY.Cause.Reason.NonPragmatic (507)TEMPORAL.Asynchronous (260)EXPANSION.Background (164)CONTINGENCY.Cause.Result.NonPragmatic (117)

Rare relations CONTINGENCY.Cause.Result.Pragmatic (4)COMPARISON.Similarity (4)EXPANSION.Exception (1)

Table 3: Statistics of the LADTB gold standard

D. Marcu. 2000. The theory and practice of discourseparsing and summarization. MIT Press.

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Connective Englishequivalent Syntactic category Type Buck-

walter ATB tag Freqð and Coordinating conj Simple wa CONJ 3826È for/of/in order to Preposition Clitic li PREP 261áºË but Coordinating conj Simple/clitic lkn CONJ 208

YªK. after Adverbial Simple/clitic bEd PREP 167

¬ then Coordinating conj Clitic fa CONJ 91àB because Subordinating conj Simple/clitic lAn CONJ 82ÉJ.

�¯ before Adverbial Simple qbl PREP 79

Q�K@ after Subordinating conj Simple Avr PREP 63

H. due to/because Preposition Clitic bi PREP 63AÒ» as/and/similarly Coordinating conj Simple kmA CONJ 60Y

JÓ since Adverbial Simple mn* PREP 59

I. �. ��. because of Prepositional phrase Simple/Paired bsbb PP PREPNOUN/PREP 45

AÓYJ« when/due Adverbial Simple EndmA CONJ 44

à@ B@ however Subordinating conj Simple AlA An EXCEPT-PART

FUNC-WORD 42ÈAg ú

¯ in case/if Prepositional phrase Simple fy HAl PREP NOUN 36

AÒJ¯ while/as Subordinating conj Simple fymA PREP

REL-PRON 36@X @ if Subordinating conj Simple/Paired A*A CONJ 31

Õç�' then Coordinating conj Simple vm ADV 30

ð@ or Coordinating conj Simple Aw CONJ 29Ñ

«P although Subordinating conj Simple/Paired rgm PREP 29

á�g ú

¯ while/in the

same time Prepositional phrase Simple/Clitic fy Hyn PREP NOUN 26AÓ@ while/as Subordinating conj Simple AmA PREP 25X @ because Coordinating conj Simple A* CONJ 21AÒÓ therefore Subordinating conj Simple mmA PP:PREP

REL-PRON 21A�ñ�

k especially Adverbial Simple xSwSA ADV SSUFF 18

AÒJ�K. while/as Subordinating conj Simple bynmA CONJ 17

Table 4: The most frequent connectives in LADTB

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