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Transformation of propositional calculus statements into integer and mixed integer programs: An approach towards automatic reformulation
A systematic procedure for transforming a set of logical statements or logical conditions imposed on a model into an Integer Linear Progamming (ILP) formulation Mixed Integer Programming (MIP) formulation is presented. An ILP stated as a system of linear constraints involving integer variables and an objective function, provides a powerful representation of decision problems through a tightly interrelated closed system of choices. It supports direct representation of logical (Boolean or prepositional calculus) expressions. Binary variables (hereafter called logical variables) are first introduced and methods of logically connecting these to other variables are then presented. Simple constraints can be combined to construct logical relationships and the methods of formulating these are discussed. A reformulation procedure which uses the extended reverse polish representation of a compound logical form is then described. These reformulation procedures are illustrated by two examples. A scheme of implementation.ithin an LP modelling system is outlined
Knowledge Rich Natural Language Queries over Structured Biological Databases
Increasingly, keyword, natural language and NoSQL queries are being used for
information retrieval from traditional as well as non-traditional databases
such as web, document, image, GIS, legal, and health databases. While their
popularity are undeniable for obvious reasons, their engineering is far from
simple. In most part, semantics and intent preserving mapping of a well
understood natural language query expressed over a structured database schema
to a structured query language is still a difficult task, and research to tame
the complexity is intense. In this paper, we propose a multi-level
knowledge-based middleware to facilitate such mappings that separate the
conceptual level from the physical level. We augment these multi-level
abstractions with a concept reasoner and a query strategy engine to dynamically
link arbitrary natural language querying to well defined structured queries. We
demonstrate the feasibility of our approach by presenting a Datalog based
prototype system, called BioSmart, that can compute responses to arbitrary
natural language queries over arbitrary databases once a syntactic
classification of the natural language query is made
On Left and Right Dislocation: A Dynamic Perspective
The paper argues that by modelling the incremental and left-right process of interpretation as a process of growth of logical form (representing logical forms as trees), an integrated typology of left-dislocation and right-dislocation phenomena becomes available, bringing out not merely the similarities between these types of phenomena, but also their asymmetry. The data covered include hanging topic left dislocation, clitic left dislocation, left dislocation, pronoun doubling, expletives, extraposition, and right node raising, with each set of data analysed in terms of general principles of tree growth. In the light of the success in providing a characterisation of the asymmetry between left and right periphery phenomena, a result not achieved in more wellknown formalisms, the paper concludes that grammar formalisms should model the dynamics of language processing in time.Articl
A Type-coherent, Expressive Representation as an Initial Step to Language Understanding
A growing interest in tasks involving language understanding by the NLP
community has led to the need for effective semantic parsing and inference.
Modern NLP systems use semantic representations that do not quite fulfill the
nuanced needs for language understanding: adequately modeling language
semantics, enabling general inferences, and being accurately recoverable. This
document describes underspecified logical forms (ULF) for Episodic Logic (EL),
which is an initial form for a semantic representation that balances these
needs. ULFs fully resolve the semantic type structure while leaving issues such
as quantifier scope, word sense, and anaphora unresolved; they provide a
starting point for further resolution into EL, and enable certain structural
inferences without further resolution. This document also presents preliminary
results of creating a hand-annotated corpus of ULFs for the purpose of training
a precise ULF parser, showing a three-person pairwise interannotator agreement
of 0.88 on confident annotations. We hypothesize that a divide-and-conquer
approach to semantic parsing starting with derivation of ULFs will lead to
semantic analyses that do justice to subtle aspects of linguistic meaning, and
will enable construction of more accurate semantic parsers.Comment: Accepted for publication at The 13th International Conference on
Computational Semantics (IWCS 2019
Interpreting Spatial Language in Image Captions
The map as a tool for accessing data has become very popular in recent years, but a lot of data do not have the necessary spatial meta-data to allow for that. Some data such as photographs however have spatial information in their captions and if this could be extracted, then they could be made available via map-based interfaces. Towards this goal, we introduce a model and spatio-linguistic reasoner for interpreting the spatial information in image captions that is based upon quantitative data about spatial language use acquired directly from people. Spatial language is inherently vague, and both the model and reasoner have been designed to incorporate this vagueness at the quantitative level and not only qualitatively
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