CarSim : automatic 3D scene generation of a car accident description

The problem of generating a 3D simulation of a car accident from a written description can be divided into two subtasks: the linguistic analysis and the virtual scene generation. As a means of communication between these two system parts, we designed a template formalism to represent a written accident report. The CarSim system processes formal descriptions of accidents and creates corresponding 3D simulations. A planning component models the trajectories and temporal values of every vehicle that is involved in the accident. Two algorithms plan the simulation of the accident. The CarSim system contains algorithms for planning collisions with static objects, as well as algorithms for modeling accidents consisting of more than one collision and collisions with vehicles which have stopped. 1

Generating a 3D Simulation of a Car Accident from a Formal Description: the CarSim System

The problem of generating a 3D simulation of a car accident from a written description can be divided into two subtasks: the linguistic analysis and the virtual scene generation. As a means of communication between these two system parts, we designed a template formalism to represent a written accident report. The CarSim system processes template formal descriptions and creates corresponding 3D simulations. A planning component models the trajectories and temporal values of every vehicle that is involved in the accident

Generating a 3D Simulation of a Car Accident from a Written Description in Natural Language: the CarSim System

This paper describes a prototype system to visualize and animate 3D scenes from car accident reports, written in French. The problem of generating such a 3D simulation can be divided into two subtasks: the linguistic analysis and the virtual scene generation. As a means of communication between these two modules, we first designed a template formalism to represent a written accident report. The CarSim system first processes written reports, gathers relevant information, and converts it into a formal description. Then, it creates the corresponding 3D scene and animates the vehicles.Comment: 8 pages, ACL 2001, Workshop on Temporal and Spatial Information Processin

Social ordering and the doctrine of free choice. The case of abjuration sub pena nubendi

One of the most important aspects of the marriage legislation in medieval canon law is the doctrine of free choice. According to this doctrine, established by pope Alexander III in the second half of the twelfth century, the validity of a marriage depended solely on the freely given consent of the parties. No one could legally force a couple to marry if they did not freely consent to do so. In parallel, any kind of sexual relations outside of marriage was prohibited by Canon Law. The most common penalty for illicit sexual relations was fines. In the case of stable relationships it was also quite common that the couple was forced to abjure one another under a sum of money. An unmarried couple could, however, also be requested to abjure one another sub pena nubendi. Abjuration sub pena nubendi meant that any future intercourse, or even its suspicion, would automatically leave a couple legally married. Abjuration sub pena nubendi developed as a means to stop illicit sexual relationships by transforming them into legal marriages. This practise was however contrary to one of the most fundamental principles of the marriage legislation in medieval Canon Law: the doctrine of free choice. In this paper I study the conflict between the idea of marriage as solely depending on free consent and the marriage coercion imposed by abjuration sub pena nubendi

Investigating multilingual dependency parsing

In this paper, we describe a system for the CoNLL-X shared task of multilingual dependency parsing. It uses a baseline Nivre’s parser (Nivre, 2003) that first identifies the parse actions and then labels the dependency arcs. These two steps are implemented as SVM classifiers using LIBSVM. Features take into account the static context as well as relations dynamically built during parsing. We experimented two main additions to our implementation of Nivre’s parser: N-best search and bidirectional parsing. We trained the parser in both left-right and right-left directions and we combined the results. To construct a single-head, rooted, and cycle-free tree, we applied the Chu-Liu/Edmonds optimization algorithm. We ran the same algorithm with the same parameters on all the languages

Natural language programming of industrial robots

In this paper, we introduce a method to use written natural language instructions to program assembly tasks for industrial robots. In our application, we used a state-of-the-art semantic and syntactic parser together with semantically rich world and skill descriptions to create highlevel symbolic task sequences. From these sequences, we generated executable code for both virtual and physical robot systems. Our focus lays on the applicability of these methods in an industrial setting with real-time constraints

Exploring Lexicalized Features for Coreference Resolution

In this paper, we describe a coreference solver based on the extensive use of lexical features and features extracted from dependency graphs of the sentences. The solver uses Soon et al. (2001)'s classical resolution algorithm based on a pairwise classification of the mentions. We applied this solver to the closed track of the CoNLL 2011 shared task (Pradhan et al., 2011). We carried out a systematic optimization of the feature set using cross-validation that led us to retain 24 features. Using this set, we reached a MUC score of 58.61 on the test set of the shared task. We analyzed the impact of the features on the development set and we show the importance of lexicalization as well as of properties related to dependency links in coreference resolution

Using WordNet to Extend FrameNet Coverage

We present two methods to address the problem of sparsity in the FrameNet lexical database. The first method is based on the idea that a word that belongs to a frame is ``similar'' to the other words in that frame. We measure the similarity using a WordNet-based variant of the Lesk metric. The second method uses the sequence of synsets in WordNet hypernym trees as feature vectors that can be used to train a classifier to determine whether a word belongs to a frame or not. The extended dictionary produced by the second method was used in a system for FrameNet-based semantic analysis and gave an improvement in recall. We believe that the methods are useful for bootstrapping FrameNets for new languages

Investigating multilingual dependency parsing

In this paper, we describe a system for the CoNLL-X shared task of multilingual dependency parsing. It uses a baseline Nivre’s parser (Nivre, 2003) that first identifies the parse actions and then labels the dependency arcs. These two steps are implemented as SVM classifiers using LIBSVM. Features take into account the static context as well as relations dynamically built during parsing. We experimented two main additions to our implementation of Nivre’s parser: N-best search and bidirectional parsing. We trained the parser in both left-right and right-left directions and we combined the results. To construct a single-head, rooted, and cycle-free tree, we applied the Chu-Liu/Edmonds optimization algorithm. We ran the same algorithm with the same parameters on all the languages