LOCALITY EFFECTS IN SENTENCE PROCESSING 43 1.2 Integration Costs

Sentence comprehension involves a whole range of processes. Amongst others, every new incoming word w has to be integrated into the current parse tree both on a syntactic and a semantic level. Structural integration involves matching syntac-tic categories of maximal projections with expectations predicted by the current partial parse tree. Syntactical integration also comprises head-dependent relation-ships such as the linking of verbs with their arguments or linking pronouns with their respective antecedents. Integration on a semantic or discourse level involves assignment of thematic roles to maximal projections. This adds information to the discourse structure. Gibson (2000) assumes that integration of new information requires a certain amount of computational resources. The amount of resources needed depends on the distance between the heads of related projections that have to be integrated with each other. This assumption bases on the logic that integrat-ing a new projection XP (headed by h₂) with a previous projection headed by h₁ can only be accomplished when grammatical information of h₁is an activated part of the working memory. Information is assumed to be an active part of working memory, if its resource activation level crosses a certain minimal threshold. As re-source capacity is limited, the DLT assumes that h₁’s activation level is subject to decay in order to release computational resources for new information. Thus, the ease of reaccessing h₁depends on its activation level which in turn depends on the amount of resources consumed in the interim between h₁and its related projection headed by h₂. As every incoming word w has to be integrated into the CPPM, every word w is a possible consumer of activation. However, Gibson (2000) states that only new discourse referents are supposed to consume computational resources.

With reference to previous work (e.g. Warren and Gibson (1999)), Gibson (2000) points out that there is a fine-grained hierarchy of accessibility. However, to simplify the DLT’s assumptions, Gibson (2000) establishes a simple and binary distinction between ‘new discourse referents’ and ‘old discourse referents’. With regard to the DRT, the DLT suggests that discourse referents are: (i) events intro-duced by verbs; (ii) entities introintro-duced by noun phrases. The model defines new discourse referents as either entities introduced with NPs or as events introduced with verbs, that can both be referred to with anaphoric expressions. Thus, the DLT only considers pronouns as old referents and subsumes all other NPs, independent of their definiteness, under the label ‘new discourse referents’.

New referents have still to be established in the discourse. Thus, processing the head h of a new discourse referent is supposed to consume a certain amount of computational resources. Words, not being the head h of an entities that introduce new discourse referents (e.g. adverbials not introducing any referent) are supposed to consume zero energy units. The same is true for referents that are already established, which are also suggested to consume zero energy units, see (8):

(8) Simplified Discourse Processing Cost:

1 energy unit (EU) is consumed if h2 is the head of a new discourse refer-ent; 0 EUs otherwise. (Gibson, 2000:104)

The costs for structural integration are assumed to increase by distance. The big-ger the distance between the head h₁ of a referent and the head h₂ of a related referent is, the more complex is the integration of h₂. Distance, as already said, is defined as the number of new discourse referents that are located between the two related referents headed by h₁and h₂. The logic for this assumption is that in order to integrate h2 into the current parse tree, information that has been intro-duced to the discourse with an earlier referent (headed by h₁), has to be retrieved from memory. In the DLT, this means that h₁ has to be reactivated above a min-imum threshold in order to be identified as part of the active working memory.

A reactivation of h₁ is necessary as the previous state of activation for h₁has de-clined to a certain degree at the point of time when h₂ is processed. As the pool of activation resources is limited, it is a logical consequence that at some point the system runs out of spare resources. In order to be able to provide upcoming new elements with activation resources, activation has to be drawn off of already processed information. Gibson (2000) assumes a decay of activation energy over time. According to the DLT, activation levels simply fade away over a very short period. The computational resources set free are available again for new referents.

Thus, with every single head h_X in the interim between two related entities, pre-viously activated information is threatened to fall under the minimum threshold.

Therefore, with an increase in distance, the ease of integrating h₁which is related to a previously activated h_Xincreases.

(9) DLT structural integration cost:

The structural integration cost associated with connecting the syntactic structure for a newly input head h2 to a projection of a head h1 that is part of the current structure for the input is dependent on the complexity of the computations that took place between h1 and h2. For simplicity, it is assumed that 1 EU is consumed for each new discourse referent in the intervening region. (Gibson, 2000:105)

The assumptions of the DLT are supported by experimental findings from a range of various linguistic phenomena. Consider, for instance, multiple center embed-ding as in (10). Accorembed-ding to Gibson (2000) the difference in processing complex-ity between the structure of a singly nested RC in (10-a) and a doubly nested RC in (10-b) are not due to incomplete dependencies as assumed in earlier hypotheses (cf. findings of Warren and Gibson, 1999 in the examples (5) - (7) above; for re-lated hypotheses, see literature cited in Gibson, 2000:98). Gibson (2000) suggests that the difference in processing complexity results from increased integration

4.1. LOCALITY EFFECTS IN SENTENCE PROCESSING 45 costs in multi center-embedded structures. Both sentences (taken from Gibson, 2000:105) consist of a matrix clause with an embedded RC (who the senator at-tacked). In the doubly nested (10-b), another RC (who John met) is embedded within the first RC.

(10) a. The reporter [ who the senator attacked ] disliked the editor.

b. The reporter [ who the senator [ who John met ] attacked ] disliked the editor.

Table 4.2 shows integration costs of the sentences in (10). For the sake of a better overview, integrations costs are broken down into (simplified) discourse process-ing costs (DPC), syntactic integration costs (SIC) and total integration costs (TIC).

DPC (introduced in (8)) assigns 1 energy unit (1 EU) for every head h₁ of a new discourse referent. SIC (introduced in (9)) assigns 1 EU to each new discourse referent in the interim between two heads (h_Xand h_Y) of two related entities. TIC is the total of both, the simplified discourse processing costs and the syntactic integration costs. Table 4.2 shows that integration costs in (10) peak at the verbs attacked and disliked. Integration costs are less high for the single nested structure in (10-a) than for the double nested structure in (10-b). This is true for both verbs.

In (10-a), total integration costs (TIC) for attacked are 3 EUs. Introducing a new discourse referent (DPC) with the event attacked costs 1 EU. Structural in-tegration (SIC) costs 2 EU and adds up as follows: integrating the senator in the subject position of attacked is cost-free, as no referent intervenes between the two items (0 EU); integrating the empty category in the object position of attacked with the previous pronoun who crosses two new discourse referents (attacked and senator) and therefore costs 2 EU. Integrating the verb disliked into the CPPM also costs 3 EUs. Construction of the new referent (DPC) costs 1 EU. Integrat-ing the verb with its argument reporter in subject position crosses two referents attacked and senator and costs 2 EU. As the editor is adjacent to disliked, its integration is cost-free (0 EU).

In (10-b) integration of attacked adds up to a total (TIC) of 7 EUs. Introduc-ing a new referent (DPC) to the discourse with the event attacked costs 1 EU.

Structural integration (SIC) of the verb attacked with its arguments senator and reporter consumes a total (TIC) of 7 EUs. Integration of attacked with senator crosses met and John and costs 2 EUs. Integration of the empty category in the ob-ject position of attacked with the previous pronoun who crosses four new referents (attacked, met, John and senator) and therefore costs 4 EUs.

TIC for disliked are 5 EUs. Constructing a new referent (DPC) with introduc-ing the event costs 1 EU. Integratintroduc-ing the verb with its argument reporter in subject position crosses four referents (attacked, met, John and senator) and costs 4 EUs.

Again, the noun editor is adjacent to disliked and its integration is cost-free.

Table 4.2: Integration Costs for Singly- versus Doubly-Nested Relative Clauses Single Nested RC

The reporter who the senator attacked disliked the editor

DPC 0 1 0 0 1 1 1 0 1

SIC 0 0 0 0 0 0 + 2 2 + 0 0 0

TIC 0 1 0 0 1 3 3 0 1

Double Nested RC

The reporter who the senator who John met attacked disliked the editor

DPC 0 1 0 0 1 0 1 1 1 1 0 1

SIC 0 0 0 0 0 0 0 1 + 0 2 + 4 4 + 0 0 0

TIC 0 1 0 0 1 0 1 2 7 5 0 1

DPC = discourse processing cost; SIC = syntactic integration cost; TIC = total integration cost

To summarize: The example in (10-b) contains two center-embedded RCs, whereas the (10-a) only contains a single center-embedded RC. Previous models of nesting complexity (for an overview of models see Gibson, 2000:98) suggested that processing complexity increases with the number of incomplete syntactic de-pendencies. Following these models, the higher processing load of (10-b) is at-tributed to more incomplete syntactic dependencies. However, such accounts fail to capture the finding that despite the structural similarity, (11) (repeats the ex-ample in (7)) is easier to process than (10-b). However, the DLT is capable of explaining this phenomenon with a higher amount of new discourse referents in (10-b). The pronoun in (11) refers to an entity that has already been established in the discourse. Therefore, crossing the pronoun I in (11) is cost-free. Crossing the new referent John in (10-b) is not cost-free.

(11) The reporter [ who the senator [ who I met ] attacked ] disliked the editor.

DLT’s predictions are capable to capture more linguistic phenomena than just sen-tences with multi embedded RCs. One phenomenon which is very well known in the sentence parsing literature is the greater complexity of object-extracted rela-tive clauses compared to subject-extracted ones (cf. Stromswold et al., 1996; Just et al., 1996)

In Table 4.3, the maximal TIC of the subject-extracted sentence occurs at the verb disliked. It takes 3 EUs to integrate the verb in the current parse tree. The sentence begins with the introduction of the first NP the reporter. Being a new referent to the discourse, establishing NP1 the reporter is associated with the cost

4.1. LOCALITY EFFECTS IN SENTENCE PROCESSING 47