This paper examines issues in parsing architecture for a left-to-right implementation of the probe-goal Case agreement model, a theory in the Minimalist Program (MP). Computation from a parsing perspective imposes special constraints. For example, in left-to-right parsing, the assembly of phrase structure must proceed through elementary tree composition, rather than using using the generative o...

Automated syntactic parsing of Philippine languages could be foundational to future machine translation systems. Rule based systems for Philippine languages have typically not reached a level of wide coverage of language phenomena. The syntax parsing system described here uses the PAWS (Parser and Writer of Syntax) expert system to generate phrase structure rules. After customized rules common ...

We tackle the problem of answer type prediction, applying a transition-based neural network parser to understand the syntactic structure of a query and infer the focus word or phrase that contains the correct type. To achive this, we first come up with a framework to combine a dataset of labeled question-answer pairs and a type inventory into a dataset to learn types. Second, we fit a sigmoid p...

In this paper, we propose a new sequential labeling scheme, double sequential labeling, that we apply it on Chinese parsing. The parser is built with conditional random field (CRF) sequential labeling models. One focuses on the beginning of a phrase and the phrase type, while the other focuses on the end of a phrase. Our system, CYUT, attended 2012 the second CIPS-SGHAN conference Bake-off Task...

This paper offers a method for the noun phrase recognition of Hungarian natural language texts based on machine learning methods. The approach learns noun phrase tree patterns described by regular expressions from an annotated corpus. The tree patterns are completed with probability values using error statistics. The noun phrase recognition parser tries to find the best-fitting trees for a sent...

Grammars or syntax specifications address themselves to the characterisation in symbolic terms of the structure of complex expressions. Two types of expression of empirical interest have been studied: sentences in English and other 'natural' languages, and programs written in some high-level procedural language like ALGOL. Expressions in these languages consist of sets of elements (words and ch...

BACKGROUND The primary method for scientific communication is in the form of published scientific articles and theses which use natural language combined with domain-specific terminology. As such, they contain free owing unstructured text. Given the usefulness of data extraction from unstructured literature, we aim to show how this can be achieved for the discipline of chemistry. The highly for...

In the state-of-the-art speech synthesis system, prosodic phrase prediction is the most serious problem which leads to about 40% of text analysis errors. Two optimization strategies are proposed in this paper to deal with two major types of prosodic phrase prediction errors. First, unsupervised adaptation method is proposed to alleviate the mismatching problem between training and testing. Seco...

There is an increasing need for automatic information extraction (IE) to support database building and to intelligently find novel knowledge of biological events from online journal collections. Many of the previous researchers (e.g., [3]) extracted such information by using hand-tailored patterns in regular expressions on some pre-defined set of verbs representing a certain type of reaction. H...

Statistical parsing of noun phrase (NP) structure has been hampered by a lack of goldstandard data. This is a significant problem for CCGbank, where binary branching NP derivations are often incorrect, a result of the automatic conversion from the Penn Treebank. We correct these errors in CCGbank using a gold-standard corpus of NP structure, resulting in a much more accurate corpus. We also imp...