Is Structure Necessary for Modeling Argument Expectations in Distributional Semantics?

Despite the number of NLP studies dedicated to thematic fit estimation, little attention has been paid to the related task of composing and updating verb argument expectations. The few exceptions have mostly modeled this phenomenon with structured distributional models, implicitly assuming a similarly structured representation of events. Recent experimental evidence, however, suggests that human processing system could also exploit an unstructured "bag-of-arguments" type of event representation to predict upcoming input. In this paper, we re-implement a traditional structured model and adapt it to compare the different hypotheses concerning the degree of structure in our event knowledge, evaluating their relative performance in the task of the argument expectations update.Comment: conference paper, IWC

The role of action representations in thematic object relations

A number of studies have explored the role of associative/event-based (thematic) and categorical (taxonomic) relations in the organization of object representations. Recent evidence suggests that thematic information may be particularly important in determining relationships between manipulable artifacts. However, although sensorimotor information is on many accounts an important component of manipulable artifact representations, little is known about the role that action may play during the processing of semantic relationships (particularly thematic relationships) between multiple objects. In this study, we assessed healthy and left hemisphere stroke participants to explore three questions relevant to object relationship processing. First, we assessed whether participants tended to favor thematic relations including action (Th+A, e.g., wine bottle—corkscrew), thematic relationships without action (Th-A, e.g., wine bottle—cheese), or taxonomic relationships (Tax, e.g., wine bottle—water bottle) when choosing between them in an association judgment task with manipulable artifacts. Second, we assessed whether the underlying constructs of event relatedness, action relatedness, and categorical relatedness determined the choices that participants made. Third, we assessed the hypothesis that degraded action knowledge and/or damage to temporo-parietal cortex, a region of the brain associated with the representation of action knowledge, would reduce the influence of action on the choice task. Experiment 1 showed that explicit ratings of event, action, and categorical relatedness were differentially predictive of healthy participants' choices, with action relatedness determining choices between Th+A and Th-A associations above and beyond event and categorical ratings. Experiment 2 focused more specifically on these Th+A vs. Th-A choices and demonstrated that participants with left temporo-parietal lesions, a brain region known to be involved in sensorimotor processing, were less likely than controls and tended to be less likely than patients with lesions sparing that region to use action relatedness in determining their choices. These data indicate that action knowledge plays a critical role in processing of thematic relations for manipulable artifacts

The Roles of Thematic Knowledge in Sentence Comprehension

People possess a great deal of knowledge concerning what commonly happens in various types of events. This knowledge, specifically with respect to event participants and their relations within an event (thematic knowledge), is an important component of how people understand language. A number of studies have shown a rapid influence of thematic knowledge during moment-to-moment sentence processing, in both investigations of lexical processing in sentential contexts, and temporary syntactic ambiguity resolution. The main goal of this dissertation is to further our understanding about the roles of thematic knowledge during sentence processing and sentence understanding by examining two critical unresolved issues. Chapter 2 investigated whether manipulation of thematic knowledge can lead to processing disruption in sentences that are otherwise assumed to be free of processing difficulty. That is, I investigated whether simple sentences can be made more difficult. This issue is particularly important for adjudicating among two major theories of sentence comprehension, two-stage and constraint-based theories. I found that main clause sentences could be made more difficult by manipulating thematic fit of the initial noun phrase, as in The host invited versus The guest invited. Because the influence of thematic fit was found at the earliest point at which it could be expected, the results strongly support constraint-based models. Chapter 3 investigated how thematic knowledge affects the construction of sentential meaning representations, and how misinterpretations can occur during that process. Specifically, the study evaluated several possibilities regarding how misanalyses of thematic roles might occur in full passive sentences that varied in plausibility. Participants’ understanding was determined by asking them to recall the agent or patient of each target sentence. The novel aspects of this study involved in-depth analyses of the types of errors that participants make, and using ERPs to investigate on-line processing differences. A major result was that the N400 ERP component was smaller for trials on which participants made an error versus when they responded correctly, indicating that errors occurred when readers were not sensitive to thematic implausibility. In summary, the studies reported in this dissertation provide novel and important theoretical insights into thematic role processing during sentence comprehension

Fitting, Not Clashing! A Distributional Semantic Model of Logical Metonymy

Logical metonymy interpretation (e.g. begin the book ->writing) has received wide attention in linguistics. Experimental results have shown higher processing costs for metonymic conditions compared with non-metonymic ones ( read the book). According to a widely held interpretation, it is the type clash between the event-selecting verb and the entity-denoting object (begin the book) that triggers coercion mechanisms and leads to additional processing effort. We propose an alternative explanation and argue that the extra processing effort is an effect of thematic fit. This is a more economical hypothesis that does not need to postulate a separate type clash mechanism: entity-denoting objects simply have a low fit as objects of event-selecting verbs. We test linguistic datasets from psycholinguistic experiments and find that a structured distributional model of thematic fit, which does not encode any explicit argument type information, is able to replicate all significant experimental findings. This result provides evidence for a graded account of coercion phenomena in which thematic fit accounts for both the trigger of the coercion and the retrieval of the covert even

Event-related brain potential evidence for animacy processing asymmetries during sentence comprehension

The animacy distinction is deeply rooted in the language faculty. A key example is differential object marking, the phenomenon where animate sentential objects receive specific marking. We used event-related potentials to examine the neural processing consequences of case-marking violations on animate and inanimate direct objects in Spanish. Inanimate objects with incorrect prepositional case marker ‘a’ (‘al suelo’) elicited a P600 effect compared to unmarked objects, consistent with previous literature. However, animate objects without the required prepositional case marker (‘el obispo’) only elicited an N400 effect compared to marked objects. This novel finding, an exclusive N400 modulation by a straightforward grammatical rule violation, does not follow from extant neurocognitive models of sentence processing, and mirrors unexpected “semantic P600” effects for thematically problematic sentences. These results may reflect animacy asymmetry in competition for argument prominence: following the article, thematic interpretation difficulties are elicited only by unexpectedly animate objects

Semantic indeterminacy in object relative clauses

This article examined whether semantic indeterminacy plays a role in comprehension of complex structures such as object relative clauses. Study 1 used a gated sentence completion task to assess which alternative interpretations are dominant as the relative clause unfolds; Study 2 compared reading times in object relative clauses containing different animacy configurations to unambiguous passive controls; and Study 3 related completion data and reading data. The results showed that comprehension difficulty was modulated by animacy configuration and voice (active vs. passive). These differences were well correlated with the availability of alternative interpretations as the relative clause unfolds, as revealed by the completion data. In contrast to approaches arguing that comprehension difficulty stems from syntactic complexity, these results suggest that semantic indeterminacy is a major source of comprehension difficulty in object relative clauses. Results are consistent with constraint-based approaches to ambiguity resolution and bring new insights into previously identified sources of difficulty. (C) 2007 Elsevier Inc. All rights reserved

Brain regions that process case: Evidence from basque

The aim of this event-related fMRI study was to investigate the cortical networks involved in case processing, an operation that is crucial to language comprehension yet whose neural underpinnings are not well-understood. What is the relationship of these networks to those that serve other aspects of syntactic and semantic processing? Participants read Basque sentences that contained case violations, number agreement violations or semantic anomalies, or that were both syntactically and semantically correct. Case violations elicited activity increases, compared to correct control sentences, in a set of parietal regions including the posterior cingulate, the precuneus, and the left and right inferior parietal lobules. Number agreement violations also elicited activity increases in left and right inferior parietal regions, and additional activations in the left and right middle frontal gyrus. Regions-of-interest analyses showed that almost all of the clusters that were responsive to case or number agreement violations did not differentiate between these two. In contrast, the left and right anterior inferior frontal gyrus and the dorsomedial prefrontal cortex were only sensitive to semantic violations. Our results suggest that whereas syntactic and semantic anomalies clearly recruit distinct neural circuits, case, and number violations recruit largely overlapping neural circuits and that the distinction between the two rests on the relative contributions of parietal and prefrontal regions, respectively. Furthermore, our results are consistent with recently reported contributions of bilateral parietal and dorsolateral brain regions to syntactic processing, pointing towards potential extensions of current neurocognitive theories of language. Hum Brain Mapp, 2012. © 2011 Wiley Periodicals, Inc

Young children's sentence comprehension: Neural correlates of syntax-semantic competition

Sentence comprehension requires the assignment of thematic relations between the verb and its noun arguments in order to determine who is doing what to whom. In some languages, such as English, word order is the primary syntactic cue. In other languages, such as German, case-marking is additionally used to assign thematic roles. During development children have to acquire the thematic relevance of these syntactic cues and weigh them against semantic cues. Here we investigated the processing of syntactic cues and semantic cues in 2- and 3-year-old children by analyzing their behavioral and neurophysiological responses. Case-marked subject-first and object-first sentences (syntactic cue) including animate and inanimate nouns (semantic cue) were presented auditorily. The semantic animacy cue either conflicted with or supported the thematic roles assigned by syntactic case-marking. In contrast to adults, for whom semantics did not interfere with case-marking, children attended to both syntactic and to semantic cues with a stronger reliance on semantic cues in early development. Children’s event-related brain potentials indicated sensitivity to syntactic information but increased processing costs when case-marking and animacy assigned conflicting thematic roles. These results demonstrate an early developmental sensitivity and ongoing shift towards the use of syntactic cues during sentence comprehension

Uniform Representations for Syntax-Semantics Arbitration

Psychological investigations have led to considerable insight into the working of the human language comprehension system. In this article, we look at a set of principles derived from psychological findings to argue for a particular organization of linguistic knowledge along with a particular processing strategy and present a computational model of sentence processing based on those principles. Many studies have shown that human sentence comprehension is an incremental and interactive process in which semantic and other higher-level information interacts with syntactic information to make informed commitments as early as possible at a local ambiguity. Early commitments may be made by using top-down guidance from knowledge of different types, each of which must be applicable independently of others. Further evidence from studies of error recovery and delayed decisions points toward an arbitration mechanism for combining syntactic and semantic information in resolving ambiguities. In order to account for all of the above, we propose that all types of linguistic knowledge must be represented in a common form but must be separable so that they can be applied independently of each other and integrated at processing time by the arbitrator. We present such a uniform representation and a computational model called COMPERE based on the representation and the processing strategy.Comment: 7 pages, uses cogsci94.sty macr

NON-PARAMETRIC STATISTICAL APPROACH TO CORRECT SATELLITE RAINFALL DATA IN NEAR-REAL-TIME FOR RAIN BASED FLOOD NOWCASTING

Floods resulting from intense rainfall are one of the most disastrous hazards in many regions of the world since they contribute greatly to personal injury and to property damage mainly as a result of their ability to strike with little warning. The possibility to give an alert about a flooding situation at least a few hours before helps greatly to reduce the damage. Therefore, scores of flood forecasting systems have been developed during the past few years mainly at country level and regional level. Flood forecasting systems based only on traditional methods such as return period of flooding situations or extreme rainfall events have failed on most occasions to forecast flooding situations accurately because of changes on territory in recent years by extensive infrastructure development, increased frequency of extreme rainfall events over recent decades, etc. Nowadays, flood nowcasting systems or early warning systems which run on real- time precipitation data are becoming more popular as they give reliable forecasts compared to traditional flood forecasting systems. However, these kinds of systems are often limited to developed countries as they need well distributed gauging station networks or sophisticated surface-based radar systems to collect real-time precipitation data. In most of the developing countries and in some developed countries also, precipitation data from available sparse gauging stations are inadequate for developing representative aerial samples needed by such systems. As satellites are able to provide a global coverage with a continuous temporal availability, currently the possibility of using satellite-based rainfall estimates in flood nowcasting systems is being highly investigated. To contribute to the world's requirement for flood early warning systems, ITHACA developed a global scale flood nowcasting system that runs on near-real-time satellite rainfall estimates. The system was developed in cooperation with United Nations World Food Programme (WFP), to support the preparedness phase of the WFP like humanitarian assistance agencies, mainly in less developed countries. The concept behind this early warning system is identifying critical rainfall events for each hydrological basin on the earth with past rainfall data and using them to identify floodable rainfall events with real time rainfall data. The individuation of critical rainfall events was done with a hydrological analysis using 3B42 rainfall data which is the most accurate product of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) dataset. These critical events have been stored in a database and when a rainfall event is found in real-time which is similar or exceeds the event in the database an alert is issued for the basin area. The most accurate product of TMPA (3B42) is derived by applying bias adjustments to real time rainfall estimates using rain gauge data, thus it is available for end-users 10-15 days after each calendar month. The real time product of TMPA (3B42RT) is released approximately 9 hours after real-time and lacks of such kind of bias adjustments using rain gauge data as rain gauge data are not available in real time. Therefore, to have reliable alerts it is very important to reduce the uncertainty of 3B42RT product before using it in the early warning system. For this purpose, a statistical approach was proposed to make near real- time bias adjustments for the near real time product of TMPA (3B42RT). In this approach the relationship between the bias adjusted rainfall data product (3B42) and the real-time rainfall data product (3B42RT) was analyzed on the basis of drainage basins for the period from January 2003 to December 2007, and correction factors were developed for each basin worldwide to perform near real-time bias adjusted product estimation from the real-time rainfall data product (3B42RT). The accuracy of the product was analyzed by comparing with gauge rainfall data from Bangladesh and it was found that the uncertainty of the product is less even than the most accurate product of TMPA dataset (3B42