This paper addresses eecient parsing in the context of logical inference for the purpose of using logic programming languages in compiler writing. A bottom-up, deterministic parsing mechanism is formulated for \bounded right context" grammars, a subclass of LR(k) grammars with characteristics amenable to declarative parser speciica-tion. A working parser generator for Prolog is described, altho...

We address the problem of joint part-of-speech (POS) tagging and dependency parsing in Chinese. In Chinese, some POS tags are often hard to disambiguate without considering longrange syntactic information. Also, the traditional pipeline approach to POS tagging and dependency parsing may suffer from the problem of error propagation. In this paper, we propose the first incremental approach to the...

We present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning techniques, the system uses parse action examples acquired under supervision to generate a determinis-tic shift-reduce parser in the form of a decision structure. It relies heavily on context , as encoded in features wh...

Recently proposed deterministic classifierbased parsers (Nivre and Scholz, 2004; Sagae and Lavie, 2005; Yamada and Matsumoto, 2003) offer attractive alternatives to generative statistical parsers. Deterministic parsers are fast, efficient, and simple to implement, but generally less accurate than optimal (or nearly optimal) statistical parsers. We present a statistical shift-reduce parser that ...

We describe a deterministic shift-reduce parsing model that combines the advantages of connectionism with those of traditional symbolic models for parsing realistic sub-domains of natural language. It is a modular system that learns to annotate natural language texts with syntactic structure. The parser acquires its linguistic knowledge directly from pre-parsed sentence examples extracted from ...

Incremental parsers have potential advantages for applications like language modeling for machine translation and speech recognition. We describe a new algorithm for incremental transition-based Combinatory Categorial Grammar parsing. As English CCGbank derivations are mostly right branching and non-incremental, we design our algorithm based on the dependencies resolved rather than the derivati...

In this paper, we present a three-step multilingual dependency parser based on a deterministic shift-reduce parsing algorithm. Different from last year, we separate the root-parsing strategy as sequential labeling task and try to link the neighbor word dependences via a near neighbor parsing. The outputs of the root and neighbor parsers were encoded as features for the shift-reduce parser. In a...

This paper presents a taxonomy of sublinear keyword pattern matching algorithms related to the Boyer-Moore algorithm [BM77) and the Commentz-Walter algorithm [CW79a, CW79b). The taxonomy includes, amongst others, the multiple keyword generalization of the single keyword Boyer-Moore algorithm and an algorithm by Fan and Su [FS93, FS94). The corresponding precomputatioD algorithms are pre~ented a...

While several approaches have been developed to enhance the efficiency of hierarchical Artificial Intelligence planning (AI-planning), complex problems in AI-planning are challenging overcome. To find a solution plan, planner produces huge search space that may be infinite. A whose small is likely more efficient than large space. In this paper, we will present new approach integrating with map-...