Length Matters: Informational Load in Ambiguity Resolution

International audienceIn this paper, we will compare prosodic and pragmatic approaches to the role of constituent length in attachment ambiguities. Lengthening a constituent affects its informativity: longer constituents are usually less predictable (Levy & Florian, 2007) and demand a higher processing load than shorter ones (Almor, 1999). Following neo-Gricean accounts (Levinson, 1987 and 1991), increased informational load needs to be justified. This justification is achieved more easily when the long constituent conveys new information and when it relates to central elements of the utterance. Informational load is, however, not a simple question of length in numbers of characters or syllables but more likely a question of amount of information. In three off-line experiments using a cloze task, we will compare the effect of lengthening ambiguous prepositional phrases as in [1a/b/c] either by lengthening a city name or by adding information about the city. We will show that only lengthening by adding information increases attachment to a more central element of the utterance. These results will be discussed based on prosodic and pragmatic factors explaining the role of constituent length for attachment ambiguities. [1] Peter met the doctor of the lawyer from a. Apt. / b. Aix-en-Provence / c. the beautiful city of Apt

CLiFF Notes: Research in the Language Information and Computation Laboratory of The University of Pennsylvania

This report takes its name from the Computational Linguistics Feedback Forum (CLIFF), an informal discussion group for students and faculty. However the scope of the research covered in this report is broader than the title might suggest; this is the yearly report of the LINC Lab, the Language, Information and Computation Laboratory of the University of Pennsylvania. It may at first be hard to see the threads that bind together the work presented here, work by faculty, graduate students and postdocs in the Computer Science, Psychology, and Linguistics Departments, and the Institute for Research in Cognitive Science. It includes prototypical Natural Language fields such as: Combinatorial Categorial Grammars, Tree Adjoining Grammars, syntactic parsing and the syntax-semantics interface; but it extends to statistical methods, plan inference, instruction understanding, intonation, causal reasoning, free word order languages, geometric reasoning, medical informatics, connectionism, and language acquisition. With 48 individual contributors and six projects represented, this is the largest LINC Lab collection to date, and the most diverse

The Effect of Prominence Hierarchies on Modern English Long Passives: Pragmatic vs. Syntactic Factors

This paper examines the effect of the most relevant crosslinguistic prominence hierarchies on long passives (or passives with an overt by-phrase), in order to identify the factors which condition their choice over actives as order-rearranging strategies in Modern English (1500-1900). With empirical data drawn from the Helsinki Corpus and ARCHER, I will study the effect of (i) familiarity hierarchies, such as given-before-new or definite-before-indefinite, (ii) dominance hierarchies, like the animacy, empathy and semantic role hierarchies, and (iii) formal hierarchies such as short-before-long. The analysis reveals a clear predominance of pragmatic and syntactic factors, namely discourse status (given-before-new) and structural complexity (short-before-long), both of which facilitate utterance planning, production and parsing. Despite the apparent correlation between these two factors, this paper also shows that they are independent and that, when in competition, discourse status is a more powerful factor than syntactic complexity

CLiFF Notes: Research in the Language, Information and Computation Laboratory of the University of Pennsylvania

One concern of the Computer Graphics Research Lab is in simulating human task behavior and understanding why the visualization of the appearance, capabilities and performance of humans is so challenging. Our research has produced a system, called Jack, for the definition, manipulation, animation and human factors analysis of simulated human figures. Jack permits the envisionment of human motion by interactive specification and simultaneous execution of multiple constraints, and is sensitive to such issues as body shape and size, linkage, and plausible motions. Enhanced control is provided by natural behaviors such as looking, reaching, balancing, lifting, stepping, walking, grasping, and so on. Although intended for highly interactive applications, Jack is a foundation for other research. The very ubiquitousness of other people in our lives poses a tantalizing challenge to the computational modeler: people are at once the most common object around us, and yet the most structurally complex. Their everyday movements are amazingly fluid, yet demanding to reproduce, with actions driven not just mechanically by muscles and bones but also cognitively by beliefs and intentions. Our motor systems manage to learn how to make us move without leaving us the burden or pleasure of knowing how we did it. Likewise we learn how to describe the actions and behaviors of others without consciously struggling with the processes of perception, recognition, and language. Present technology lets us approach human appearance and motion through computer graphics modeling and three dimensional animation, but there is considerable distance to go before purely synthesized figures trick our senses. We seek to build computational models of human like figures which manifest animacy and convincing behavior. Towards this end, we: Create an interactive computer graphics human model; Endow it with reasonable biomechanical properties; Provide it with human like behaviors; Use this simulated figure as an agent to effect changes in its world; Describe and guide its tasks through natural language instructions. There are presently no perfect solutions to any of these problems; ultimately, however, we should be able to give our surrogate human directions that, in conjunction with suitable symbolic reasoning processes, make it appear to behave in a natural, appropriate, and intelligent fashion. Compromises will be essential, due to limits in computation, throughput of display hardware, and demands of real-time interaction, but our algorithms aim to balance the physical device constraints with carefully crafted models, general solutions, and thoughtful organization. The Jack software is built on Silicon Graphics Iris 4D workstations because those systems have 3-D graphics features that greatly aid the process of interacting with highly articulated figures such as the human body. Of course, graphics capabilities themselves do not make a usable system. Our research has therefore focused on software to make the manipulation of a simulated human figure easy for a rather specific user population: human factors design engineers or ergonomics analysts involved in visualizing and assessing human motor performance, fit, reach, view, and other physical tasks in a workplace environment. The software also happens to be quite usable by others, including graduate students and animators. The point, however, is that program design has tried to take into account a wide variety of physical problem oriented tasks, rather than just offer a computer graphics and animation tool for the already computer sophisticated or skilled animator. As an alternative to interactive specification, a simulation system allows a convenient temporal and spatial parallel programming language for behaviors. The Graphics Lab is working with the Natural Language Group to explore the possibility of using natural language instructions, such as those found in assembly or maintenance manuals, to drive the behavior of our animated human agents. (See the CLiFF note entry for the AnimNL group for details.) Even though Jack is under continual development, it has nonetheless already proved to be a substantial computational tool in analyzing human abilities in physical workplaces. It is being applied to actual problems involving space vehicle inhabitants, helicopter pilots, maintenance technicians, foot soldiers, and tractor drivers. This broad range of applications is precisely the target we intended to reach. The general capabilities embedded in Jack attempt to mirror certain aspects of human performance, rather than the specific requirements of the corresponding workplace. We view the Jack system as the basis of a virtual animated agent that can carry out tasks and instructions in a simulated 3D environment. While we have not yet fooled anyone into believing that the Jack figure is real , its behaviors are becoming more reasonable and its repertoire of actions more extensive. When interactive control becomes more labor intensive than natural language instructional control, we will have reached a significant milestone toward an intelligent agent

Alternating ditransitives in English: a corpus-based study

This thesis is a large-scale investigation of ditransitive constructions and their alternants in English. Typically both constructions involve three participants: participant A transfers an element B to participant C. A speaker can linguistically encode this type of situation in one of two ways: by using either a double object construction or a prepositional paraphrase. This study examines this syntactic choice in the British component of the International Corpus of English (ICE-GB), a fully tagged and parsed corpus incorporating both spoken and written English. After a general introduction, chapter 2 reviews the different grammatical treatments of the constructions. Chapter 3 discusses whether indirect objects have to be considered necessary complements or optional adjuncts of the verb. I then examine the tension between rigid classification and authentic (corpus) data in order to demonstrate that the distinction between complements and adjuncts evidences gradient categorisation effects. This study has both a linguistic and a methodological angle. The overall design and methodology employed in this study are discussed in chapter 4. The thesis considers a number of variables that help predict the occurrence of each pattern. The evaluation of the variables, the determination of their significance, and the measurement of their contribution to the model involve reliance on statistical methods (but not statistical software packages). Chapters 5, 6, and 7 review pragmatic factors claimed to influence a speaker’s choice of construction, among them the information status and the syntactic ‘heaviness’ of the constituents involved. The explanatory power and coverage of these factors are experimentally tested independently against the corpus data, in order to highlight several features which only emerge after examining authentic sources. Chapter 8 posits a novel method of bringing these factors together; the resulting model predicts the dative alternation with almost 80% accuracy in ICE-GB. Conclusions are offered in chapter 9

Right Association Revisited

Considerations of when Right Association works and when it fails lead to a restatement of this parsing principle in terms of the notion of heaviness. A computational investigation of a syntactically annotated corpus provides evidence for this proposal and suggests circumstances when RA is likely to make correct attachment predictions. 1 Introduction Kimball (1973) proposes the parsing strategy of Right Association (RA). RA resolves modifiers attachment ambiguities by attaching at the lowest syntactically permissible position along the right frontier. Many authors (among them Wilks 1985, Schubert 1986, Whittemore et al. 1990, and Weischedel et al. 1991) incorporate RA into their parsing systems, yet none rely on it solely, integrating it instead with disambiguation preferences derived from word/constituent/concept co-occurrence based. On its own, RA performs rather well, given its simplicity, but it is far from adequate: Whittemore et al. evaluate RA's performance on PP attachment usi..