Juraj Dzifcak
Solving puzzles described in English by automated translation to answer set programming and learning how to do that translation.
Mon, 08/22/2011 - 15:01 — SomNambulAuthors: Chitta Baral, Juraj Dzifcak
Subjects: Computation and Language (Computational Linguistics and Natural Language and Speech Processing)
AbstractWe present a system capable of automatically solving combinatorial logic
puzzles given in (simplified) English. It involves translating the English
descriptions of the puzzles into answer set programming(ASP) and using ASP
solvers to provide solutions of the puzzles. To translate the descriptions, we
use a lambda-calculus based approach using Probabilistic Combinatorial
Categorial Grammars (PCCG) where the meanings of words are associated with
parameters to be able to distinguish between multiple meanings of the same
word. Meaning of many words and the parameters are learned.Using Inverse lambda and Generalization to Translate English to Formal Languages.
Mon, 08/22/2011 - 15:01 — SomNambulAuthors: Chitta Baral, Juraj Dzifcak, Marcos Alvarez Gonzalez, Jiayu Zhou
Subjects: Computation and Language (Computational Linguistics and Natural Language and Speech Processing)
AbstractWe present a system to translate natural language sentences to formulas in a
formal or a knowledge representation language. Our system uses two inverse
lambda-calculus operators and using them can take as input the semantic
representation of some words, phrases and sentences and from that derive the
semantic representation of other words and phrases. Our inverse lambda operator
works on many formal languages including first order logic, database query
languages and answer set programming.Language understanding as a step towards human level intelligence - automatizing the construction of the initial dictionary from example sentences.
Mon, 08/22/2011 - 15:01 — SomNambulAuthors: Chitta Baral, Juraj Dzifcak
Subjects: Computation and Language (Computational Linguistics and Natural Language and Speech Processing)
AbstractFor a system to understand natural language, it needs to be able to take
natural language text and answer questions given in natural language with
respect to that text; it also needs to be able to follow instructions given in
natural language. To achieve this, a system must be able to process natural
language and be able to capture the knowledge within that text. Thus it needs
to be able to translate natural language text into a formal language. We
discuss our approach to do this, where the translation is achieved by composing
the meaning of words in a sentence.
User login
