Syntactic composition and selectional preferences in H indi Light Verb Constructions (2019)

Abstract: Previous work on light verb constructions (e.g. chorii kar ‘theft do; steal’) in Hindi describes their syntactic formation via co-predication (Ahmed et al., 2012, Butt, 2014). This implies that both noun and light verb contribute their arguments, and these overlapping argument structures must be composed in the syntax. In this paper, we present a co-predication analysis using Tree-Adjoining Grammar, which models syntactic composition and semantic selectional preferences without transformations (deletion or argument identification). The analysis has two key components (i) an underspecified category for the nominal and (ii) combinatorial constraints on the noun and light verb to specify selectional preferences. The former has the advantage of syntactic composition without argument identification and the latter prevents over-generalization, while recognizing the semantic contribution of both predicates. This work additionally accounts for the agreement facts for the Hindi LVC.

## introduction light verb constructions have been defined as "two (or more) predicational elements that each contribute to a joint predication" @xcite . a light verb construction e.g. give a kiss consists of a 'light' verb give and a second predicating element viz. the noun kiss. in comparison to the simple event verb kiss, the light verb construction has a more nuanced meaning, where there is a 'transfer' of the kiss from giver to receiver. the verb give in this light verb construction contributes this meaning, which is more abstract as compared to its ordinary lexical usage as give in give a book. light verb constructions (henceforth, lvcs) are found across languages such as japanese, korean, persian and english as well as german. in languages like hindi, urdu and persian, these constructions are particularly pervasive. lvcs in hindi are often subsumed under the term 'complex predicates' because light verbs in hindi can combine with another verb, an adjective, adverb or even a borrowed english verb or noun. complex predication of this sort is highly productive in hindi, as well as other south asian languages @xcite . in this paper, we continue to refer to predicating noun and light verb combinations as 'light verb constructions', though they are also sometimes referred to as 'support verb' or 'complex verb' constructions. one of the primary syntactic challenges for lvcs is monoclausality with two predicating heads. for simple predicates, such as the examples seen in ( 1 ) and (2), a single set of semantic roles will map to their respective grammatical functions. e.g. subject and object to agent and patient respectively. in the case of lvcs as seen in (3), two predicating heads will result in a composite argument structure (see also figure 1 ). this 'division of labour' problem, where the correct roles mapped to correct grammatical functions must eventually surface in a monoclausal structure is precisely the reason for the plethora of operations required for lvc analysis. previous work e.g. argument transfer @xcite states that the number of arguments 'transferred' to the light verb can only take place in a particular order (agents before themes, for example). some analyses e.g. @xcite have considered the light verb to be a form of auxiliary. this allows the light verb construction to remain monoclausal without having to posit two predicating elements. @xcite have argued that in fact light verbs in south asian languages have been historically stable, and not subject to phonological attrition or semantic bleaching, which are characteristics of auxiliaries. further arguments for monoclausality have shown that light verb constructions have a single subject in the clause @xcite . this implies that the syntactic representation must allow the representation of the argument structures of both the light verb and the predicating noun. another fallout of the monoclausality problem is the treatment of the light verb as simply a theta marker of arguments, which contributes nothing at all to the event description. @xcite and others describe predicate 'bleaching', where the light verb is stripped of any semantic contribution. the term 'bleaching' is somewhat misleading, as it does seem that the light verb contributes a core meaning e.g. volitionality, forcefulness, surprise or transfer @xcite . going further, this meaning constrains the range of possible light verb constructions as well. for example, make a mistake is acceptable but not *take a mistake. @xcite has shown that nouns that are semantically similar tend to co-ocur with the same light verb. such a semantic constraint explains the patterns of acceptable combinations in hindi as well and this needs to be represented in the analysis. previous work on light verb constructions has increasingly turned to lexicalized grammars to address these questions. lexicalized grammars have been used for linguistically precise representations and are particularly useful with respect to phenomena that interact with valence @xcite . before we turn to our tree-adjoining grammar analysis, we examine an existing analysis of lvcs in lexical-functional grammar. when light verbs occur, they trigger a process of argument merger because they appear with an incomplete argument structure frame. below, we show the a-structures for the noun and light verb as seen in example (4). the % notation stands for a variable whose value will be supplied by the noun's argument structure. the resulting merger of the two argument structures results in the composite argument structure of the lvc. in order to compose the argument structure from the two copredicators, a restriction operator is used to manipulate the f-structure @xcite . the ability to restrict (non-monotonically affect) certain features allows the manipulation of the f-structure (valency property) of the light verb. the restriction operator identifies the noun as the %pred value in the light verb's a-structure. the lowest matrix argument for do as seen in figure 2 is identified with the highest embedded argument, which is also an agent @xcite . now, there are three arguments to be linked at the level of f-structure using the linking relations that connect the grammatical functions subj, obj with the thematic roles indicated by the features @xcite . the highest (and only) @xcite argument is linked to subj by the mapping principles @xcite . the instrumental argument gets @xcite and is linked to obl. the object is @xcite and is linked to obj. note that in this example, the light verb shows agreement with the predicating noun, hence it acts both as the obj of the lvc, as well as predicate. in light verb constructions, the light verb will agree with the nominal, provided no other argument in the sentence has nominative (null) case (example (4)). for simple predicates, the verb will always agree with the highest nominative (null) marked argument, which is not necessarily the syntactic subject. in simple verbs, in examples (5) and ( 6 ), the nominative argument is the subject and the object respectively. in example (7), there is no nominative argument available, thus the verb shows 'default' agreement with third person, masculine, singular. nouns such as bahas 'quarrel' in the example (4) also have another property-the light verb agrees with the predicating nominal bahas in number and gender. therefore, the nominal is simultaneously an argument and a part of the lvc. the f-structure in figure 3 shows the composed argument structure with the predicating noun. the hallmark of this analysis is that the in this paper, we propose that lvcs are formed via syntactic composition, but our analysis separates the monoclausal requirement of the lvc and the semantic contribution of the light verb. in the lfg account, maintaining mono-clausality without a deletion rule and argument identification becomes a difficult task. instead of combining two sets of argument structures, we design a single initial tree which contains all the arguments, but an underspecified category (i.e. it is not the elementary tree for the 'predicating noun'). we show that we can represent the lvc's argument structure using such a representation. further, we describe our analysis of the acceptability of noun and light verb combinations based on their semantic properties. we incorporate this into our analysis using features, which will permit the appropriate combination of two predicating elements to take place. in the following sections, we briefly introduce the tag formalism that we will use and then motivate our tag proposal. we then describe the design for the elementary trees in tag and conclude with a summary and discussion of our work. ## introduction to lexicalized tree-adjoining grammar we briefly introduce the tree-adjoining grammar formalism that we use in this section. tree-adjoining grammar (tag) is a formal treerewriting system that is used to describe the syntax of natural languages @xcite . the primitive of a tag grammar is an elementary tree, which is a fragment of a phrase structure tree labelled with both terminal and non-terminal nodes. the elementary trees are combined by the operations of substitution (where a terminal node is replaced with a new tree) or adjunction (where an internal node is split to add a new tree, see also fig 4 ). the elementary trees in tag can be enriched with feature structures @xcite . these can capture linguistic descriptions in a more precise manner and also capture adjunction constraints. tag with feature structures is also known as ftag (feature-structure based tag). a tag can also be lexicalized i.e. each elementary tree has at least one lexical item as one of its terminal nodes. lexicalized tag enhanced with feature structures is known as lexicalized featurebased tree-adjoining grammar (lf-tag). this has been used for developing computational grammars for english @xcite , french @xcite and korean @xcite . in our analysis, we will also use lf-tag, but we will refer to it as ltag for convenience. figure 4 shows the basic steps for composing elementary trees containing feature structures. unless it is a substitution node, each node has a top and a bottom feature structure. features can be shared among nodes in an elementary tree. in the tree for the verb running, the variable 1 is used to show that the verb must share the same features as the subject np. the tree for running is an initial tree with a single terminal for its argument noun phrase (np). the tree for is, on the other hand, is a special type of elementary tree called the auxiliary tree. it has a foot node (marked with an asterisk), whose labels are identical to its root node. the auxiliary tree will adjoin into the tree for running at the vp s vp ltag showing feature structures and constraints on adjunction (example adapted from @xcite ). the topmost trees show the operations of substitution (solid line) and adjunction (dashed line). following these operations, we get a complete sentence 'jill is running'. after both top and bottom nodes unify, the derivation is complete. during adjunction, the top feature structure at vp r in the auxiliary tree (for is) will unify with the top of the adjunction site (vp). the bottom feature structure at vp r in the auxiliary tree will unify with the bottom of the adjunction site. during substitution, the top node in the tree for jill unifies with the node at np in the initial tree for running. this results in the second tree in figure 4 , post the operations of substitution and adjunction. in a final derivation step, top and bottom feature structures at each node will unify, to give the final derived tree with a single feature structure at each node. the resulting tree is called a derived tree, but another by-product of the tag analysis is also the derivation tree. this tree has numbered node labels that record the history of composition of the elementary trees. for example, the tree for jill is running can be seen in figure 5 . the root of this tree is labelled with running, which is an initial tree of type s. ## the tag proposal the tag analysis that follows assumes that the lvc formation takes place at the syntactic rather than the lexical level. this is based on evidence that the lvc is syntactically flexible although it forms a single meaningful unit. in this respect, lvcs are similar to verb-particle constructions, or decomposable idioms @xcite . in general, tests for light verb constructions cannot include standard surface constituency diagnostic tests e.g. adjacency, scrambling, negation or adverbial modification @xcite . rather, the real diagnostic test is whether the two predicates result in one event, which may not be modified separately @xcite . on the other hand, the fact that light verb constructions express a single event has also resulted in proposals to treat the lvc as a single lexical entry. @xcite analyze the persian lvc as a 'construction' in the construction grammar framework. in their analysis, all lvcs are understood as being non-compositional, as both noun and light verb do not contribute a consistent meaning for every lvc combination. in effect, every lvc forms a separate lexical entry. in terms of tag, this gives us two options, first an analysis where the nominal projects all the arguments of the lvc, and is the initial tree for the construction. the second option is to represent both components as anchors of a single elementary tree-a single multi-word expression. previous tag analyses for english lvcs have both nominal and verb as anchors in the same elementary tree @xcite ) and the arguments simply substitute into this tree. figure 6 shows the derivation trees (cf. figure 5 ) for the analysis options as described above for example (9). the lvc in question is chorii kar 'theft do'. the dashed line indicates adjunction into the elementary tree, whereas the solid line indicates substitution. in the noun-centric analysis, the light verb adjoins into the nominal's elementary tree. for the multi-word expression tree, theft and do are both anchors of the elementary tree. for the purposes of this paper (and the tag analyses that follow), we focus on lvcs that do not have idiomatic meanings or incorporation. such lvcs contain event nouns that subcategorize for their own arguments and combine with the light verb to form a single 'compositional' meaning. it seems reasonable that for such nouns, there is syntactic composition of the argument structures of both noun and light verb. recent psycholinguistic evidence, both from behavioural data as well noun as @xmath0.fsg) multi-word @xmath1.perf.fsg) @xmath2. the lvc is chorii kii. as erp studies show that lvcs are likely to be constructed 'online', rather than being retrieved as single lexical entries like ordinary predicates. processing light verb constructions incurs an additional cost, measured in reaction time differences and sustained neural activity after the onset of the verb @xcite . this evidence strengthens the idea that non-idiomatic lvcs are likely to be composed in the syntax. we also note that hindi allows scrambling (movement) of nps before the verb, and that scrambling can also affect the predicating noun. for example, it's possible to scramble (9) as (10). for such cases, it would be necessary to extend the ltag analysis, similar to previous work done for german (for example @xcite , @xcite ). in the work on german, elementary trees are replaced by sets or trees with underspecified dominance. in order to account for scrambling, we will need to assume an analysis using sets of trees (e.g. multi-component tag or mc-tag). in the work on german, the source of predication does not move, since in german this is the verb. foot_0 however, we can simply add an initial tree with a trace which is co-indexed with the predicating noun. the predicating noun and its arguments are all treated as separate auxiliary trees in the same treeset. the use of feature structures can be carried over to the multi component approach, since feature values can be co-indexed among different trees of the same set. this approach forces the syntactic realization of the predicate-argument structure, but allows for complete freedom of order among the arguments and the predicating noun (also across clause boundaries). we omit further details here. in the following sections, we motivate the design of the elementary trees for the nominal and the light verb. we look at the underspecified category of the nominal and the feature structures that specify selectional preferences and agreement facts. ## an example in this section, we will show a worked-out example of the syntactic composition of noun and light verb. in this example, elementary trees for nominal tareef 'praise' and light verb 'do' are composed. in (17) the lvc's composite argument structure has the agent subject logon and the theme pustak. while the former has verbal case, the latter has genitive case and is an argument introduced by the predicating noun tareef. figure 8 tree for nominal t "areef 'praise' (agentive), as seen in logon ne pustak kii t "areef kii "people praised the book". the feature clash at xp1 is marked with a box. the nominal in figure 8 has the composite argument structure for tareef 'praise', with an @xmath3. it is an initial tree anchored by the lexical item tareef and the non terminals at np  and np  are marked with a ↓ for substitution with the actual lexical items. np  requires the ergative-marked agent argument. agentive arguments would be found in combination with the @xmath4. np  in figure 8 has the features for [@xmath5. the agentive argument shares the values for perf and agt with the xp  node. this ensures that the light verb that adjoins into this tree will match the perf and agt values in np  . the value for nagr is positive as the light verb shows agreement with the nominal tareef for this example. other arguments at np  and np  will not have an agr feature unless they have nominative (null) case. when nagr is positive, agr gets its features from the nominal and these are passed up to the place of adjunction. when the light verb's agreement with the noun is not possible, e.g. if a higher nominative argument is available, the agr feature will be populated by that argument. the value of nagr can also be negative if the light verb does not agree with the nominal (or agrees only optionally). we explore these cases in more detail in the following sections. the elementary tree for the nominal is not complete, because of the feature clash at xp  between [@xmath6. [@xmath7. this will force adjunction of the light verb into the nominal's tree. xp r @xmath8.f.sg.prf) xp f @xmath9.f.sg.prf' the light verb's tree will adjoin into the tree of the nominal. in order to model the light verb kar 'do' in example (18), we will construct an auxiliary tree, anchored at kar 'do' as shown in figure 9 . the light verb kar is inflected for person, number, and gender as well as tense and aspect. in this particular example, it is tensed, feminine, singular and has perfective aspect; therefore it appears as kii, and its agr value also has the correct feature fsg. in figure 9 , the xp r (root) node and its right-branching daughters are @xcite with linguistic information about gender, number, tense and aspect. the feature @xmath10.the xp f (foot) node has [@xmath11, which will enable it to adjoin into the elementary tree of a nominal. the case value is specified as nom (nominative) as the light verb will assign nominative case to the noun. figure 10 shows the tree post adjunction, and figure 11 shows the composed argument structure post substitution and unification of the paired feature structures at each node. xp  @xmath12.perf.fem.sg) xp f @xmath13. xp  @xmath14 after adjunction, substitution and feature structure unification, we get the complete argument structure. substitution at the nodes np1 and np2 gives us logon-ne pustak-kii tareef kii 'people praised the book' ## summary in our paper, we outlined two challenges for the formal description of lvc formation: a process of syntactic composition that required the merging of two predicate heads in a single clause, and second a process of semantic combination that checked the compatibility of the noun and verb's semantic features. using an underspecified cateogory and feature structures within tag, we are able to capture the argument structure properties, alternations and agreement facts for the lvc. the process of syntactic composition as described in this analysis specifies each alternation on both the predicating nominal and the light verb. this is possible using the two operations of adjunction and substitution with complex elementary tree structures and is in keeping with the tag maxim of "complicate locally, simplify globally" @xcite . from the point of view of tag grammar extraction, the particular design of the elementary tree for the nominal maps directly to the subcategorization frames in hindi propbank @xcite . the nominal is also specified for all the arguments of the complex predicate in these frames, and this will directly help to determine the number of substitution nodes for the nominal's elementary tree. elementary trees extracted from existing noun frames will eliminate an extra rule-writing step to extract predicate heads and their argu-ments from the hindi treebank. instead, it would be possible to utilize hand-corrected frame files for elementary tree generation. these, in conjunction with phrase-structure conversion rules could be used to extract automatically tag grammars from the hindi treebank @xcite .