Víctor J. Díaz

Relating tabular parsing algorithms for LIG and TAG

Tree Adjoining Grammars (TAG) and Linear Indexed Grammars (LIG) are extensions of Context Free Grammars that generate the class of Tree Adjoining Languages. Taking advantage of this property, and providing a method for translating a TAG into a LIG, we define several parsing algorithms for TAG on the basis of their equivalent LIG parsers. We also explore why some practical optimizations for TAG parsing cannot be applied to the case of LIG.

Mixed Parsing of Tree Insertion and Tree Adjoining Grammars

Adjunction is a powerful operation that makes Tree Adjoining Grammar (TAG) useful for describing the syntactic structure of natural languages. In practice, a large part of wide coverage grammars written following the TAG formalism is formed by trees that can be combined by means of the simpler kind of adjunction defined for Tree Insertion Grammar. In this paper, we describe a parsing algorithm that makes use of this characteristic to reduce the practical complexity of TAG parsing: the expensive standard adjunction operation is only considered in those cases in which the simpler cubic-time adjunction cannot be applied.

A Review of Early-Based Parser for TIG

Tree Insertion Grammar (TIG) is a compromise between Context-Free Grammars (CFG) and Tree Adjoining Grammars (TAG), that combines the efficiency of the former with the strong lexicalizing power of the latter. In this paper, we present a plain representation of TIG elementary trees that can be used directly as the input grammar for the original Earley parser without the additional considerations established in the Schabes and Waters Earley-based parser for TIG.

Improving the Performance of a Named Entity Extractor by Applying a Stacking Scheme

In this paper we investigate the way of improving the performance of a Named Entity Extraction (NEE) system by applying machine learning techniques and corpus transformation. The main resources used in our experiments are the publicly available tagger TnT and a corpus of Spanish texts in which named entities occurrences are tagged with BIO tags. We split the NEE task into two subtasks 1) Named Entity Recognition (NER) that involves the identification of the group of words that make up the name of an entity and 2) Named Entity Classification (NEC) that determines the category of a named entity. We have focused our work on the improvement of the NER task, generating four different taggers with the same training corpus and combining them using a stacking scheme. We improve the baseline of the NER task (F β =1 value of 81.84) up to a value of 88.37. When a NEC module is added to the NER system the performance of the whole NEE task is also improved. A value of 70.47 is achieved from a baseline of 66.07.

Bidirectional push down automata

We define a new model of automata for the description of bidirectional parsing strategies for context-free grammars and a tabulation mechanism that allow them to be executed in polynomial time. This new model of automata provides a modular way of defining bidirectional parsers, separating the description of a strategy from its execution.

Left Corner Parser for Tree Insertion Grammars

Tree Adjoining Grammar (TAG) is a grammar formalism that has become very popular for the description of natural languages, however, this context-sensitive formalism entails important computation costs (O(n6)-time). Tree Insertion Grammar (TIG) is a compromise between Context Free Grammar (CFG) and TAG that can be parsed in O(n3) - time. In the literature, just two Earley-like parsers for TIGs have been defined. In this paper, we define a new variant of Earley-like parser for TIGs. In order to improve the performance of this parser, we show how the left corner relation for CFG can be generalized to the case of TIG and we present an efficient parser for TIG that uses this relation.Tree Adjoining Grammar (TAG) is a grammar formalism that has become very popular for the description of natural languages, however, this context-sensitive formalism entails important computation costs (O(n6)-time). Tree Insertion Grammar (TIG) is a compromise between Context Free Grammar (CFG) and TAG that can be parsed in O(n3) - time. In the literature, just two Earley-like parsers for TIGs have been defined. In this paper, we define a new variant of Earley-like parser for TIGs. In order to improve the performance of this parser,w e show how the left corner relation for CFG can be generalized to the case of TIG and we present an efficient parser for TIG that uses this relation.