contains a second-order generalization, in addition to the first-order generalization. What the standard notation for generalization is designed to do, and indeed excels at, is displaying propositional structure. It graphically represents how the force, scope and order components interact to make up propositions expressing generalization, and it allows us to typify these propositions in a compl...

Studies examining friendships among Mexican-American adolescents have largely focused on their potentially negative influence. The current study examined the extent to which deviant and achievement-oriented friend affiliations are associated with Mexican-American adolescents' school adjustment and also tested whether support from friends and parents moderates these associations. High school stu...

The paper presents an outline of a unified answer to five questions concerning logic: (1) Is logic in themind or in theworld? (2)Does logic need a foundation? What is the main obstacle to a foundation for logic? Can it be overcome? (3) How does logic work?What does logical form represent? Are logical constants referential? (4) Is there a criterion of logicality? (5)What is the relation between ...

AnswerFinder combines lexical, syntactic, and semantic information in various stages of the question answering process. The candidate sentences are preselected on the basis of (i) the presence of named entity types compatible with the expected answer type, and (ii) a score combination of the overlap of words, grammatical relations, and flat logical forms. The candidate answers, in turn, are ext...

We distill Penrose’s argument against the “artificial intelligence premiss”, and analyze its logical alternatives. We then clarify the different positions one can take in answer to the question raised by the argument, skirting the issue of introspection per se.

This paper describes the retrieval experiments for the main task and list task of the TREC-10 questionanswering track. The question answering system described automatically finds answers to questions in a large document collection. The system uses a two-stage retrieval approach to answer finding based on matching of named entities, linguistic patterns, and keywords. In answering a question, the...

We present a question answering system that combines information at the lexical, syntactic, and semantic levels, in the process to find and rank the candidate answer sentences. The candidate exact answers are extracted from the candidate answer sentences by means of a combination of information-extraction techniques (named entity recognition) and patterns based on logical forms. The system part...

In this paper we present a graph-based approach to question answering. The method assumes a graph representation of question sentences and text sentences. Question answering rules are automatically learnt from a training corpus of questions and answer sentences with the answer annotated. The method is independent from the graph representation formalism chosen. A particular example is presented ...

We introduce the language LP that extends logic programs under the stable model semantics to allow weighted rules similar to the way Markov Logic considers weighted formulas. LP is a proper extension of the stable model semantics to enable probabilistic reasoning, providing a way to handle inconsistency in answer set programming. We also show that the recently established logical relationship b...

Classically, a computation operates on a string of bits, applying a sequence of physically realizable operations (such as logical NOT, AND, and OR), and outputs an answer based on the value of the last obtained bit string. Similarly, a quantum computation operates on a register consisting of a number of quantum bits (qubits), applying a sequence of (hypothetically) physically realizable quantum...