by E JEZEK · Cited by 17 — (e.g. to event-selecting verbs like concludere, riprendere). Most notably, light verbs (dare, fare, tenere etc.), i.e. verbs that typically combine with.

178 KB – 9 Pages

PAGE – 1 ============
When GL meets the corpus: a data-driven investigation of semantic types and coercion phenomena Elisabetta JEZEK University of Pavia, Dept. of Linguistics Strada Nuova 65 Pavia, Italy, 27100 jezek@unipv.it Alessandro LENCI University of Pisa, Dept. of Linguistics Via Santa Maria 36 Pisa, Italy, 56126 alessandro.lenci@ilc.cnr.it Abstract In this paper we present an analysis of corpus- derived V-Object combinations aiming to provide a data-driven characterization of Semantic Types (STs) and improve our understanding of how types behave compositionally, i.e. how they enter compositional processes and are modulated by them. As a theoretical framework, we adopt the enriched compositional rules and the type system as presented in Pustejovsky (2007). Our main concerns are twofold: i.) first of all, we will show with a specific case-study how a data-driven investigation can shed light on the organization of the type system and on semantic compositional operations affecting types; ii.) starting from the results of this investigation, we intend to propose a general methodology for lexical modeling in which the Generative Lexicon (GL) theory and corpus analysis are deeply interwoven in a process of mutual feeding. In fact, we argue that, if on the one hand corpus data can help to anchor the study of lexical dynamics and type system on empirical evidence, on the other hand GL can provide the crucial interpretative key for corpus data. 1 Theoretical background One of the major developments of the GL theory in recent years has been the integration of the type system into a theory of argument selection where what counts for compositional rules is the correspondence between the type selected by the predicate and the type of the argument(s) (Pustejovsky 2001, 2007). Types may be of three main sorts: simple -, unified Рand dot-types . Simple types correspond to natural types, e.g. lion, rock, water, etc. Unified types extend simple types with telic and/or agentive dimensions, and essentially correspond to types of artifactual entities and/or entities inherently endowed with a specific functionality, e.g. knife, beer, teacher, etc. Finally, dot types correspond to intrinsically polysemous types (e.g. school, book , etc.), obtained through a complex type-construction operation on natural and unified types. This tripartite type system also applies to verbs and adjectives, which express simple, unified or dot predicative functions depending on the type of the argument they select. What triggers semantic operations such as coercion is precisely the syntagmatic clash between selecting and selected type. When it occurs, this clash may fail completely to assign an interpretation to the combination (as in the case of *the rock died ) or it may give rise to two kinds of coercion operations: exploitation and introduction . In the first case, some component of the lexical meaning is accessed and exploited, whereas in the second case, some new conceptual material is introduced contextually. Globally, the theory now predicts 9 possible domain-preserving operations on types, as reported in Table 1. Next to operations on types, GL syntagmatic processes also include co-composition phenomena between V and argument, which license new interpretations of the predicate in context. Since both operations of typing and co-composition may take place simultaneously on the same syntagmatic sequence, the picture of what goes on where in a word combination, as far as the construction of its meaning goes, is not an easy one to reconstruct. Type selected Argument type Simple (natural) Unified (artifactual) Dot (complex) Simple (natural) Selection Introduction Introduction Unified (artifactual) Exploitation Selection Introduction Dot (complex) Exploitation Exploitation Selection Table 1 ΠComposition operations on types in GL

PAGE – 2 ============
2 Why and how is corpus evidence crucial for a GL-like semantic theory? Corpora have often been regarded as a precious source of evidence to feed GL-like lexical models. Various corpus-based techniques have been applied to learn qualia structure information from corpora (cf. Bouillon et al. 2002; Yamada & Baldwin 2004). Pustejovsky et al. (2004) present a strategy to develop a corpus-driven type system through the use of Corpus Pattern Analysis (CPA), an approach to which the present research is explicitly and most directly related. CPA is a semi- automatic bootstrapping process to produce a dictionary of selection contexts for predicates in a language (Hanks & Pustejovsky 2005). Corpus- derived syntagmatic patterns are mapped onto GL as a linguistic model of interpretation, which guides and constrains the induction of word senses from distributional information. In our research we apply the basic ideas of CPA to explore the organization of the type system and its qualia articulation, as well as the compositional operations that act on STs. Notwithstanding the richness of evidence on word behavior it provides, the use of corpus analysis raises the crucial issue of how to properly map the extracted patterns onto the GL architecture of the lexicon. Let us call a given predicative complex V-N extracted from a corpus such as or < read Œbook obj>, etc. Each is a piece of observed evidence of the distribution of lexical items in context. The key epistemological issue is thus the following: what kind of inferences we can draw from the extracted contexts about the type system and the compositional rules? Given a certain context that we observe in a corpus, we have to ask ourselves three sorts of related but independent qu estions: i.) what is the type of N? ii.) what is the type selected by the V? iii.) what is the particular operation that allowed N and V to compose semantically in ? Our claim is that these three questions can be answered by investigating the combinatorial distributions of V and N in a corpus. We assume that the combinatorial distribution of a lexical item is determined and constrained by its type and that for this reason it can be taken as an empirical indicator of what the type is. We expect lexical items belonging to same type to show a similar syntagmatic distribution and differences in distribution to be indicators of differences in type (although we will see later that this assumption is sometimes too strong and needs to be restrained). Notice that this strategy differs radically from other approaches that assume that the type of a given lexical item is provided by a fixed, corpus- independent, fully-fledge d ontology of semantic types such as for instance WordNet (Fellbaum, 1998). Although we are not against the idea of adopting a predefined ontology of semantic types, we believe this should ra ther be conceived as a shallow repository of semantic types (much in the style of the Brandeis Shallow Ontology , as described in Pustejovsky et al. 2006), that represent the starting point for a corpus-based definition of fine-grained STs emerging as abstractions over the combinatorial patterns of lexical items. We thus propose that by inspecting a reasonably large amount of syntagmatic contexts extracted form a corpus it is possible to draw a more detailed map of a GL-style lexical type system. The key point is that any attempt to get at a data- driven characterization of STs can not dispense with a careful analysis of the compositional operations between types, which are responsible for the empirical distribution of V-N pairs we observe in corpora. Given GL architecture, we have to assume that each context pair has been generated by the combina tions of two different factors: i.) the structure of the STs to which V and N in belong, as well as their position in the overall type system; ii.) the particular semantic operations that have driven the semantic composition of V and N in . If represents our empirical observational datum, i.) and ii.) are the two hidden parameters that we have to discover. As we said above in §. 1, given the assumption that compositionality is not driven by pure type selection only, the challenge for any corpus-based approach to GL is exactly how to reconstruct the complex interplay between the type system and the array of semantic operations on types that we have to assume as being operative in every syntagmatic context. 3 Corpus processing and data extraction In this research we focus our attention on Italian data, although we believe that most of our claims extend to other languages quite straightforwardly. Our dataset includes 877,352 syntagmatic contexts of V-N pairs, in which N is either the subject (374,948) or the direct object (502,404) of V. In this paper we have focused only on V-obj contexts. Each token has been automatically extracted from a 20 million subset of the La Repubblica Corpus, a 450 million word corpus of written Italian newspaper articles (Baroni et al. 2004). The corpus subset has been automatically processed

PAGE – 3 ============
with IDEAL+ (Bartolini et al. 2004), a rule-based, finite-state dependency par ser for Italian. From the parser outputs we extracted the context pairs that we used to build lexical sets for nouns and verbs. Following Hanks & Pustejovsky (2005), and Hanks (2006), we define the lexical set LS for a noun N (or for a verb V) as the list of verbs (nouns) with which the noun (verb) typically occurs as direct object. In other words, LSs are paradigmatic series of words that can occupy the same syntagmatic position (either as argument or predicate). We will see later how this notion is crucial in our investigation. In order to anchor the notion of typical co-occurrence on firmer quantitative grounds, we used log-likelihood (Dunning 1993) to measure the strength of association between each V and N type in our dataset. The elements of LS of a noun N with the highest log-likelihood score therefore represent the most typical predicates with which N occurs as direct object: we will refer to such sets as verbal LSs. Symmetrically, the elements of LS of a verb V with the highest log-likelihood score are the most typical nouns that occur as direct objects of V; these sets will be referred below as nominal LSs. Although we are perfectly aware that our definitions of and of LS abstract away from many important features of the whole word context (e.g. the presence of other arguments, modifiers, etc.), they nevertheless reveal interesting properties of the lexical type system, as our analysis below will show. 4 Anatomy of a type: the case of leggere fireadfl The rest of this paper is devoted to present a case study in which the methodology illustrated above is applied to an in-depth analysis of the semantic type associated with the verb leggere fireadfl. In particular, in this section we aim at showing how the nouns appearing in the LS of this verb can be projected on a GL ontology of semantic types described in terms of their qualia structure, while in §. 5 the same empirical data will provide evidence for a more complex articulation of the lexical type system. In §. 6, corpus analysis will be used to explore the operations proposed in GL to describe the compositional dynamics between predicates and their arguments. First of all, why leggere? The reason of choosing this verb as the starting point for our case study of a specific semantic type is that its English equivalent read is a predicate whose selective environment is prima facie fairly well- characterized within GL. In fact, it is defined as a complex functional type selecting for a complex, dot-argument as its direct object: y:phys info x:eN [read(x,y)]. This analysis is motivated by the fact that fithe concept of reading is sui generis to an entity that is defined as ‚informational print matters™, that is, a complex type such as phys infofl (Pustejovsky 2007: 29). Consequently, given the battery of semantic operations illustrated in §. 1 above, we expect pure selection to apply between read and whatever lexical item that is an instance of this dot-type. The prototypical case of this sort of composition occurs in the phrase read the book : fithe predicate read requires a dot object of type phys info as its direct object, and the NP present, the book, satisfies this typing directlyfl (ibid.: 32). Lexical sets as defined in §. 3 can be used to carry out a sort of fiautoptic analysisfl of types in order to evaluate whether our intuition about the selective environment of leggere is validated and simultaneously refined with the help of text-driven data. To this purpose, we extracted from our dataset the nominal LS of leggere, which includes the most typical nouns occurring as direct object of this predicate in our corpus. In Table 2 we reported the top 40 nouns of this nominal LS, ordered by decreasing log-likelihood (ll) values. If we look at this table, we immediately see that the lexical set of nouns combining with leggere does not directly map to a single semantic type, and that from the fact that a noun is included in the nominal lexical set of leggere, we can not simply infer that the type of the noun is phys info. The reason for this is twofold, and is consistent with GL predictions: first of all, leggere has the ability not only to combine by pure selection, but also to coerce the argument type. This is the case for instance of person names like Freud and Rimbaud occurring in the nominal LS of leggere, and that are clearly coerced to be interprete d as the works written by these authors. Secondly, leggere can itself undergo co-compositions when combining with an argument that does not match its selective requirements and licence different meanings, as in the case of leggere il pensiero , where leggere = ‚interpret™ Taking this into account, it becomes cleat that the analysis of LS brings afore a truly general methodological issue, i.e. what does the fact of observing a given noun within the lexical set of a verb tell us about the noun™s type as well as its internal structure ? We would like to claim that this problem can be dealt with by reversing the perspective of the analysis and inspecting the composition of the verbal LSs of the nouns, looking at two aspects simultaneously: the selectional properties of the verbs, and their association strength (ll value). This actually means that we have to explore a larger area of the combinatorial space of lexical items: i.e. we can try

PAGE – 4 ============
noun ll value noun ll value noun ll value libro fibookfl 225,44 cartella fipagefl 40,64 missiva fimissivefl 15,85 giornale finewspaperfl 174,98 messaggio fimessagefl 36,10 telegramma fitelegramfl 14,97 articolo fiarticlefl 133,28 relazione fireportfl 35,14 poesia fipoemfl 14,77 lettera filetterfl 96,77 passo fipassagefl 34,60 verdetto fiverdictfl 14,62 romanzo finovelfl 76,63 resoconto fireportfl 30,04 brano fipassagefl 14,62 testo fitextfl 58,34 parola fiwordfl 29,71 nota finotefl 14,51 documento fidocumentfl 56,42 frase fisentencefl 28,75 opera fiworkfl 14,20 intervista fiinterviewfl 52,37 sentenza fisentencefl 25,93 Rimbaud 14,19 comunicato ficommuniquéfl 49,23 motivazione fireasonfl 23,39 sofisma fisophismafl 14,19 dichiarazione fistatementfl 48,07 Freud 19,96 Tuttosport 14,19 pagina fipagefl 47,76 Financial Times 19,40 scritta fiwriting, noticefl 11,75 sceneggiatura fiscriptfl 44,17 omelia fisermonfl 16,92 telex fitelexfl 11,59 riga filinefl 42,03 notizia finewsfl 16,14 discorso fispeechfl 41,07 saggio fiessayfl 16,04 Table 2 – top 40 nouns in the LS of leggere libro fibookfl articolo fiarticlefl testo fitextfl scrivere fiwritefl scrivere fiwritefl pubblicare fipublishfl leggere fireadfl leggere fireadfl approvare fiapprovefl pubblicare fipublishfl pubblicare fipublishfl votare fivotefl presentare fipresentfl inviare fisendfl leggere fireadfl sfogliare fileaf throughfl ricevere fireceivefl modificare fimodifyfl dedicare fidedicatefl abrogare ficancelfl scrivere fiwritefl riscrivere firewritefl applicare fienforcefl redigere fiwritefl tradurre fitraslatefl dedicare fidedicatefl emendare fiamendfl ristampare fireprintfl approvare fiapprovefl preparare fipreparefl vendere fisellfl bocciare firejectfl diffondere ficirculatefl romanzo finovelfl lettera filetterfl messaggio fimessagefl scrivere fiwritefl inviare fisendfl inviare fisendfl leggere fireadfl scrivere fiw ritefl lanciare fisendfl pubblicare fipublishfl ricevere fireceivefl mandare fisendfl ristampare fireprintfl spedire fisendfl ricevere fireceivefl concepire ficonceivefl leggere fireadfl consegnare fideliverfl intitolare figive a titlefl mandare fis endfl trasmettere fitransmitfl pianificare fiplanfl recapitare fid eliverfl intercettare fiinterceptfl filmare fifilmfl consegnare fid eliverfl leggere fireadfl comprare fibuyfl pubblicare fipublishfl portare fibringfl finire fifinishfl firmare fisi gnfl recapitare fideliverfl Table 3 – top 10 verbs in the LS of a set of nouns in the LS of leggere to gain some insights about the selecting type of a predicate V by looking at the other verbs {Vij,–,Vkj} with which a noun N j combines, with Nj a member of the nominal LS of V. Notice, however, that this operation is not straightforward for the same reason we mentioned for leggere. Verbal LSs may contain two sorts of verb: best verbs, i.e. verbs that match the noun type and combine by pure selection, and coercing verbs, i.e. verbs that do not match the noun type and coerce it either via exploitation or introduction. Within the most frequent , we can thus expect to find both these verbs, although in principle we assume introductions to be more likely situated in low frequencies of . Keeping this in mind, we have extracted the verbal LS of a subset of 6 nouns co-occurring with leggere in Table 2. These nouns are: libro fibookfl, articolo fiarticlefl, testo fitextfl, romanzo finovelfl , lettera filetterfl, messaggio fimessagefl. For reasons of space, we have reported in Table 3 only the top 10 verbs (ordered for decreasing ll values) of the verbal LSs of these nouns. The analysis of these LSs bring afore interesting regularities and enables us to identify two first subsets of nouns, which we discuss below: – libro fibookfl, articolo fiarticlefl, testo fitextfl, romanzo finovelfl. The verbal LSs of these nouns all share the fact of being characterized by verbs expressing acts of composing or using semiotic artifacts in which the printed dimension is at least as salient as the informational one. In fact, in the top ranks of these LSs we find verbs expressing variations of writing (e.g. scrivere , riscrivere , etc.), reading (leggere, rileggere , leggiucchiare, etc.) and printing (e.g. pubblicare , stampare, ristampare, etc.);

PAGE – 5 ============
– lettera filetterfl and messaggio fimessagefl. This set is also characterized by verbal LSs dominated by verbs selecting the physical and the informational dimensions. However, now the physical dimension is not selected by events of writing or printing, but rather by events of transmission and exchange (e.g. mandare, inviare , spedire, ricevere , etc.). From this first piece of analysis, we can conclude that there are reasons to believe that these nouns all belong to the type phys info , since they all typically co-occur with verbs selecting for phys info or, alternatively, with verbs selecting for the physical dimension ( portare, posare ) or the informational one ( criticare, censurare, votare) . However, the question arises how we can account for the differences in their LSs. It is evident that types are not sufficient to account for the whole syntagmatic distribution of these nouns: they do not capture all facets of the semantic of these lexical items. We claim that GL model can provide the right interpretive key for such distributional facts and that the differences in the lexical sets of these nouns can be accounted for in terms of differences in their qualia specifications. Therefore, we believe that the following type representation would be appropriate for the two subsets of nouns discussed above (using the notation of tensor types in Pustejovsky 2007): (1) libro fibookfl, articolo fiarticlefl, romanzo finovelfl, testo fitextfl: phys info Telic READING _EVENTS {read , reread,–} Agentive WRITING _EVENTS {write , rewrite, –} Agentive PUBLISHING _EVENTS {publish , print , –} (2) lettera filetterfl, messaggio fimessagefl: phys info Telic READING_EVENTS {read, reread,–} Telic TRANSMISSION _EVENTS {send, circulate , deliver–} Agentive WRITING _EVENTS {write, modify , –} Agentive PUBLISHING _EVENTS {publish , –} The representations in (1 ) and (2) also closely correspond to most natural intuitions about the semantics of a noun like letter : a letter, like a book is an artifact created with the purpose of being read. However, the former also differs from the latter because a letter has a further telic dimension concerning transmission: something is not a letter, unless it is designed in such a way that it can be sent or exchanged. Besides, nouns such as articolo and testo also exhibit in their verbal LS a number of verbs expressive events of the legislative domain (e.g. approvare, votare, etc.): in fact within the realm of written semiotic artifacts we should account for those endowed with normative and performative character. It is worth emphasizing that these data call for much more advanced models of the type system than those simply couched in terms of ta xonomic structures and the like. In this respect, a system like GL, in which fine-grained distinctions can be captured by the way qualia information enters into the type constitution, is able to offer more promising accounts of noun (and verb) semantic properties as emerging from their distributional behaviour. 5 Discovering lexical types Besides providing a refined representation of the nouns as far as their qualia structure is concerned (§. 4), the investigation of the verbal LSs also allows us to confirm empirically our assumptions that the nouns of the verbal LS of leggere do not all belong to the same type. Consider again the nouns discussed in the previous sections and compare them to the verbal LSs of giornale finewspaperfl on the one side, and to intervista fiinterviewfl, discorso fispeechfl, dichiarazione fideclarationfl reported in Table 4. Although all the nouns in this latter group share leggere as one of their most frequent co-occurring verbs, the composition of their verbal LSs differs radically from the ones of the nouns in Table 3. If we look at the verbal LS of giornale , the presence of verbs that typically select for humans or organizations – like querelare fibring an action againstfl, dirigere fieditfl, attaccare fiattackfl and obbligare fiforcefl clearly bring afore an additional key aspect of the polysemy of this noun, i.e. its organizational dimension, that is not at all shared by the lexemes discussed in §. 4. This confirms and at the same time supports our intuition that giornale is actually part of a more complex dot type than phys info, i.e. organization (phys info), and that its representation should therefore be the following: (3) giornale finewspaperfl: organization (phys info Telic READING _EVENTS {read, } Agentive PUBLISHING _EVENTS {publish, print, – }) Telic AGENTIVE _EVENTS {edit, attack, } Let us now look at the verbal LS of intervista fiinterviewfl, discorso fi speechfl, and dichiarazione fideclarationfl in Table 4. What immediately comes into sight is that the physical and/or printed dimension is now in the background: although these nouns co-occur with verbs selecting for physical objects and informational content, they very often combine with verbs that select for the oral/sound dimension (e.g. pronunciare, ascoltare, registrare, etc.) or for the eventive, time enduring

PAGE – 6 ============
giornale finewspaperfl intevista fiinterviewfl dichiarazione fideclarationfl discorso fispeechfl leggere fireadfl rilasciare figivefl rilasciare fimakefl pronunciare fipronouncefl scrivere fiwritefl concedere figivefl fare fimakefl riprendere ficontinuefl stampare fiprintfl leggere fireadfl diffondere ficirculatefl fare fimakefl sfogliare fileaf through dare figivefl leggere fireadfl tenere figivefl leggiucchiare fireadfl mandare fisendfl presentare fipresentfl leggere fireadfl querelare fibring an actionfl pubblicare fipublishfl firmare fisignfl allargare fienlarge rileggere fire-readfl rileggere firereadfl sottoscrivere fiendorsefl pronunziare fipronouncefl attaccare fiattackfl realizzare fimakefl smentire firefutefl ascoltare filistenfl dirigere fieditfl raccogliere ficollectfl consegnare fideliverfl rivolgere fiaddressfl riempire fifillfl registrare firecordfl interpretare fiinterpretfl concludere ficoncludefl Table 4 – top 10 verbs in the LS of a set of nouns of the LS of leggere character of the entities to which the nouns refer to (e.g. to event-selecting verbs like concludere, riprendere). Most notably, light verbs ( dare, fare, tenere etc.), i.e. verbs that typically combine with nouns denoting events, also occupy a central position in the verbal LSs of these nouns. We claim that the reason why it is so is that these nouns are in fact first of all events with certain temporal duration in which an amount of information is exchanged, primarily orally. This does not imply that interviews, speeches and declarations can not be written or read, but that this dimensions might not be part of their intrinsic denotation. Rather, we would claim that with these nouns the written, physical dimension is coerced, or better introduced to them, by specific verbs, such as write or read, that can occur with them, and that the type associated to these nouns is event info . As in §. 4, we can express the semantic properties of these nouns w ith the following type representation (using the notation of tensor types in Pustejovsky 2007): (4) discorso fispeechfl, intervista fiinterviewfl dichiarazione fideclarationfl: event info Agentive SPEECH_EVENTS {pronounce , address , give a speech –} Telic LISTENING _EVENTS {listen , –} To sum up, from the analysis of the verbal LSs carried out in §. 4 and 5, we may conclude that the variations in the verbal LSs can be interpreted as an indicator of two main facts: differences in qualia specifications or difference in type . Although some exceptions can de detected, and although we are perfectly aware that our analysis above greatly underestimates the complexity of the lexical type space, our investigation so far shows that the assumptions about what the type of a noun is are sensibly confirmed by and reflected in its syntagmatic behaviour, and that the method of combinatorial analysis of LSs that we have sketched here offers a promising perspective to integrate type system investigation with corpus analysis. 6 An overall map of compositional operations Besides allowing us to confirm or falsify our hypotheses about what the semantic type associated to specific nouns is, corpus analysis can help us to improve our understanding of how types behave compositionally, and thus to contribute to represent how the meaning of a V-N combination is computed. As we already clarified, our starting assumption is that a key property of types is their ability to undergo modifi cations (coercions) in context, thus expanding exponentially the creative ways in which we can use them to express meanings. Also, following Pustejovsky (2007), we assume that predicates act ivate coercions on types if these latter do not correspond to the selectional restrictions. We would like to claim that it is precisely these assumptions that corpus analysis can help us to verify, possibly giving us new insights on how we can approach these problems. Taking Table 1 as the skeleton of our analysis, we see that the GL organization of the type system makes two specific predictions concerning the compositional modes of dot-types, with respect to domain preserving operations: i.) a dot-argument will compose either by pure selection, with a dot- predicate, or by exploitation, with a natural or artifactual selecting predicates (third row of Table 1); ii.) a dot-selecting predicate will compose either by pure selection, with a matching dot- argument, or by introduction, with natural and artifactual arguments (third column of Table 1). Corpus data can be used to verify to what extent these predictions are borne out. To test the first prediction, we use the verbal LSs of the nouns discussed above, that as a result of our analysis in §. 4 and 5 have been assigned either to the phys info type (e.g. libro, romanzo, articolo, testo, lettera, messaggio ) or to the event info type (e.g. intervista, discorso , dichiarazione), or to the organization (phys info ) type (i.e. giornale). These LSs show that prediction i.) is substantially confirmed. In fact, we can find verbs that either match the dot type perfectly (i.e. select

PAGE – 8 ============
libro ambientare (fisetfl) terminare (fifinishfl), cominciare (fistartfl) romanzo finire (fifinishfl), cominciare (fistartfl) articolo concludere (ficoncludefl), iniziare (fistartfl), cominciare (fibeginfl), terminare (fifinishfl), chiudere (ficlosefl) testo completare (ficompletefl), finire (fifinishfl) lettera concludere (ficoncludefl), terminare (fifinishfl), interrompere (fiinterruptfl), finire (fifinishfl) messaggio concludere (fifinishfl), cominciare (fistartfl), finire (fifinishfl) Table 7 Œ Domain-shifting introduction of events In order to account for coercions across domains (involving dot objects), we need to postulate an ordered sequence of co mpositional operations. First, an event is introduced through predicate selection: secondly, the Agentive and/or Telic specifications of the qualia structure of the nouns are exploited. Coming now to prediction ii.), we can test it by analyzing the nominal LS of leggere, as a prototypical case of dot-selecting predicate. Again, the prediction is essentially confirmed by the data, with introduction working side by side to selection as the typical compositional operations of this predicate. An operation of exploitation is also detected (dot exploitation), occurring when the constituents of the dot-type of the noun match only partially the constituents of the dot-type selected by the predicate, as in leggere il giornale, where both the types phys and info are exploited, but not organization . selection leggere un libro (fibookfl), un ar ticolo (fiarticlefl), un romanzo (finovelfl), una lettera (filetterfl) dot-exploitation leggere un giornale (finewspaperfl) introduction phys: leggere la trama (fiplotfl), la musica (fimusicfl), un film (fimoviefl), un discorso (fispeechfl) info leggere la mano (fiha ndfl), leggere una lapide (fiheadstonefl), un dispositivo (fidevicefl), un contatore (fimeterfl) phys and info leggere l™anima (fisoulfl), gli umori (fimoodfl) Table 8 Œ semantic operations in the nominal LS of leggere As for introductions, in some cases ( leggere la trama, la musica ) the verb introduces a physical, written dimension, while in others ( leggere la mano, il contatore ) a physical artifact is coerced into an entity endowed with informational content. Finally, in a number of instances ( leggere l™anima, gli umori), both the physical and the informational dimensions seem to be simultaneously wrapped around the argument by the predicate. Notice, however, that the interpretation of these last examples is complicated by the fact that, as we already clarified in §. 4, next to activating typing operations, leggere itself can undergo co- compositions with the argument and licence new senses. In these last exam ples, for instance, we could assume that the meaning of leggere differs from the one it exhibits in leggere il libro etc. (=come to know the info contained in a physical object), and is close to a more abstract sense of interpreting, decoding, etc. Thus, instead of the verb introducing a physical dimension onto the nouns, the latter would act on the reverse way, co- composing with the verb to determine its specific sense in context. The corpus provides other even clearer instances of co-composition, such as leggere una radiografia (= interpret) and leggere una favola a un bambino (= talk it loud). These facts might suggest that the problem of disambiguating between coercions and co- compositions is a truly theoretical issue that can not be directly answered by looking at distributional evidence in a corpus only. Corpus analysis could provide us with quantitative data concerning the distribution in contexts of a specific sense of a predicate. On other hand, a clear understanding of the differences between co- compositions and coercions will require that other factors are taken into account as well, such as for instance the computational costs that are associated with different compositional operations (e.g. introductions being more costly then exploitations). 7 Final remarks and future research Although we are aware that we have barely scratched the surface of the complex organization of even the small lexical fragment that we presented above, we think we can conclude that the combinatorial analysis of LSs is a promising method to integrate type system inquiry with corpus processing. So far, we can say that this technique has allowed us to: i) confirm our assumptions about what the semantic type of a given N is; b) refine the representation of the qualia structure of N; c) investigate empirically operations of coercion and co-composition. At a more general level, the results of our research confirms the possibility establishing a virtuous circle of mutual feeding between corpus analysis and GL. Infact, on the one hand, GL mechanisms

178 KB – 9 Pages