Classifying Standard Linguistic Processing Functionalities based on Fundamental Data Operation Types
نویسندگان
چکیده
It is often argued that a set of standard linguistic processing functionalities should be identified, with each of them given a formal specification. We would benefit from the formal specifications; for example, the semi-automated composition of a complex language processing workflow could be enabled in due time. This paper extracts a standard set of linguistic processing functionalities and tries to classify them formally. To do this, we first investigated prominent types of language Web services/linguistic processors by surveying a Web-based language service infrastructure and published NLP toolkits. We next induced a set of standard linguistic processing functionalities by carefully investigating each of the linguistic processor types. The standard linguistic processing functionalities was then characterized by the input/output data types, as well as the required data operation types, which were also derived from the investigation. As a result, we came up with an ontological depiction that classifies linguistic processors and linguistic processing functionalities with respect to the fundamental data operation types. We argue that such an ontological depiction can explicitly describe the functional aspects of a linguistic processing functionality.
منابع مشابه
How DoesStrawson Unify Epistemology, Ontology and Logic
Strawson’s conception of analysis as a ‘connective linguistic analysis’ makes it possible for him to achieve an indefinitely large range of ideas or concepts among them are certain numbers of fundamental, general and pervasive concepts or concept-types which not only are pre-theoretical or ahistorical, but also together constitute a structural framework only within whichlogic, ontology and epis...
متن کاملروش جدید متنکاوی برای استخراج اطلاعات زمینه کاربر بهمنظور بهبود رتبهبندی نتایج موتور جستجو
Today, the importance of text processing and its usages is well known among researchers and students. The amount of textual, documental materials increase day by day. So we need useful ways to save them and retrieve information from these materials. For example, search engines such as Google, Yahoo, Bing and etc. need to read so many web documents and retrieve the most similar ones to the user ...
متن کاملNamed Entity Recognition in Persian Text using Deep Learning
Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...
متن کاملCrosslingual Countability Classification: English meets Dutch
This paper presents a range of methods for classifying Dutch nouns as countable, uncountable or plural only based on both Dutch and English data. The classification is based on the occurrence of countability specific linguistic features that are extracted from unannotated corpora. We show that in the absence of reliable Dutch gold standard data, cross-linguistic classification can be achieved o...
متن کاملTool of the Intelligence Economic: Recognition Function of Reviews Critics - Extraction and Linguistic Analysis of Sentiments
This paper describes the part of recommender system designed for movies’ critics recognition. Such a system allows the automatic collection, evaluation and rating of critics and opinions of the movies. First the system searches and retrieves texts supposed to be movies’ reviews from the Internet. Subsequently the system carries out an evaluation and rating of movies’ critics. Finally the system...
متن کامل