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Chunking (computational Linguistics)
Shallow parsing (also chunking or light parsing) is an analysis of a sentence which first identifies constituent parts of sentences (nouns, verbs, adjectives, etc.) and then links them to higher order units that have discrete grammatical meanings (noun groups or phrases, verb groups, etc.). While the most elementary chunking algorithms simply link constituent parts on the basis of elementary search patterns (e.g., as specified by regular expressions), approaches that use machine learning techniques (classifiers, topic modeling, etc.) can take contextual information into account and thus compose chunks in such a way that they better reflect the semantic relations between the basic constituents. That is, these more advanced methods get around the problem that combinations of elementary constituents can have different higher level meanings depending on the context of the sentence. It is a technique widely used in natural language processing. It is similar to the concept of lexical ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parsing
Parsing, syntax analysis, or syntactic analysis is a process of analyzing a String (computer science), string of Symbol (formal), symbols, either in natural language, computer languages or data structures, conforming to the rules of a formal grammar by breaking it into parts. The term ''parsing'' comes from Latin ''pars'' (''orationis''), meaning Part of speech, part (of speech). The term has slightly different meanings in different branches of linguistics and computer science. Traditional Sentence (linguistics), sentence parsing is often performed as a method of understanding the exact meaning of a sentence or word, sometimes with the aid of devices such as sentence diagrams. It usually emphasizes the importance of grammatical divisions such as subject (grammar), subject and predicate (grammar), predicate. Within computational linguistics the term is used to refer to the formal analysis by a computer of a sentence or other string of words into its constituents, resulting in a par ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Association For Computational Linguistics
The Association for Computational Linguistics (ACL) is a scientific and professional organization for people working on natural language processing. Its namesake conference is one of the primary high impact conferences for natural language processing research, along with EMNLP. The conference is held each summer in locations where significant computational linguistics research is carried out. It was founded in 1962, originally named the Association for Machine Translation and Computational Linguistics (AMTCL). It became the ACL in 1968. The ACL has a European (EACL), a North American ( NAACL), and an Asian (AACL) chapter. History The ACL was founded in 1962 as the Association for Machine Translation and Computational Linguistics (AMTCL). The initial membership was about 100. In 1965, the AMTCL took over the journal '' Mechanical Translation and Computational Linguistics''. This journal was succeeded by many other journals: the '' American Journal of Computational Linguistics'' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Named-entity Recognition
Named-entity recognition (NER) (also known as (named) entity identification, entity chunking, and entity extraction) is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names (PER), organizations (ORG), locations (LOC), geopolitical entities (GPE), vehicles (VEH), medical codes, time expressions, quantities, monetary values, percentages, etc. Most research on NER/NEE systems has been structured as taking an unannotated block of text, such as transducing: into an annotated block of text that highlights the names of entities: In this example, a person name consisting of one token, a two-token company name and a temporal expression have been detected and classified. Problem Definition In the expression '' named entity'', the word ''named'' restricts the task to those entities for which one or many strings, such as words or phrases, stand (fairly) consistentl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantic Role Labeling
In natural language processing, semantic role labeling (also called shallow semantic parsing or slot-filling) is the process that assigns labels to words or phrases in a sentence that indicates their semantic role in the sentence, such as that of an agent, goal, or result. It serves to find the meaning of the sentence. To do this, it detects the arguments associated with the predicate or verb of a sentence and how they are classified into their specific roles. A common example is the sentence "Mary sold the book to John." The agent is "Mary," the predicate is "sold" (or rather, "to sell,") the theme is "the book," and the recipient is "John." Another example is how "the book belongs to me" would need two labels such as "possessed" and "possessor" and "the book was sold to John" would need two other labels such as theme and recipient, despite these two clauses being similar to "subject" and "object" functions. History In 1968, the first idea for semantic role labeling was prop ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Parser
Parsing, syntax analysis, or syntactic analysis is a process of analyzing a string of symbols, either in natural language, computer languages or data structures, conforming to the rules of a formal grammar by breaking it into parts. The term ''parsing'' comes from Latin ''pars'' (''orationis''), meaning part (of speech). The term has slightly different meanings in different branches of linguistics and computer science. Traditional sentence parsing is often performed as a method of understanding the exact meaning of a sentence or word, sometimes with the aid of devices such as sentence diagrams. It usually emphasizes the importance of grammatical divisions such as subject and predicate. Within computational linguistics the term is used to refer to the formal analysis by a computer of a sentence or other string of words into its constituents, resulting in a parse tree showing their syntactic relation to each other, which may also contain semantic information. Some parsing a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
NLTK
The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language. It supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning functionalities. It was developed by Steven Bird and Edward Loper in the Department of Computer and Information Science at the University of Pennsylvania. NLTK includes graphical demonstrations and sample data. It is accompanied by a book that explains the underlying concepts behind the language processing tasks supported by the toolkit, plus a cookbook. NLTK is intended to support research and teaching in NLP or closely related areas, including empirical linguistics, cognitive science, artificial intelligence, information retrieval, and machine learning. NLTK has been used successfully as a teaching tool, as an individual study tool, and as a platform for prototyping and building r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
General Architecture For Text Engineering
General Architecture for Text Engineering (GATE) is a Java suite of natural language processing (NLP) tools for man tasks, including information extraction in many languages. It is now used worldwide by a wide community of scientists, companies, teachers and students. It was originally developed at the University of Sheffield beginning in 1995. As of May 28, 2011, 881 people are on the gate-users mailing list at SourceForge.net, and 111,932 downloads from SourceForge are recorded since the project moved to SourceForge in 2005. The paper "GATE: A framework and graphical development environment for robust NLP tools and applications" has received over 2000 citations since publication (according to Google Scholar). Books covering the use of GATE, in addition to the GATE User Guide, include "Building Search Applications: Lucene, LingPipe, and Gate", by Manu Konchady, and "Introduction to Linguistic Annotation and Text Analytics", by Graham Wilcock. GATE community and research has been ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
OpenNLP
The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as language detection, tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing and coreference resolution. These tasks are usually required to build more advanced text processing services. See also * Unstructured Information Management Architecture (UIMA) * General Architecture for Text Engineering General Architecture for Text Engineering (GATE) is a Java suite of natural language processing (NLP) tools for man tasks, including information extraction in many languages. It is now used worldwide by a wide community of scientists, companies, t ... (GATE) * cTAKES References External linksApache OpenNLP Website {{Apache Software Foundation Natural language processing Statistical natural language processing Natural language processing toolkits OpenNLP Java (programming ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Second Language
A second language (L2) is a language spoken in addition to one's first language (L1). A second language may be a neighbouring language, another language of the speaker's home country, or a foreign language. A speaker's dominant language, which is the language a speaker uses most or is most comfortable with, is not necessarily the speaker's first language. For example, the Canadian census defines first language for its purposes as "What is the language that this person first learned at home in childhood and still understands?", recognizing that for some, the earliest language may be lost, a process known as language attrition. This can happen when young children start school or move to a new language environment. Second-language acquisition The distinction between acquiring and learning was made by Stephen Krashen as part of his monitor theory. According to Krashen, the ''acquisition'' of a language is a natural process; whereas ''learning'' a language is a conscious one. In ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sentence (linguistics)
In linguistics and grammar, a sentence is a Expression (linguistics), linguistic expression, such as the English example "The quick brown fox jumps over the lazy dog." In traditional grammar, it is typically defined as a string of words that expresses a complete thought, or as a unit consisting of a Subject (grammar), subject and Predicate (grammar), predicate. In non-functional linguistics it is typically defined as a maximal unit of syntactic structure such as a Constituent_(linguistics), constituent. In functional linguistics, it is defined as a unit of written texts delimited by writing, graphological features such as upper-case letters and markers such as periods, question marks, and exclamation marks. This notion contrasts with a curve, which is delimited by phonologic features such as pitch and loudness and markers such as pauses; and with a clause, which is a sequence of words that represents some process going on throughout time. A sentence can include words grouped meaning ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lexical Analysis
Lexical tokenization is conversion of a text into (semantically or syntactically) meaningful ''lexical tokens'' belonging to categories defined by a "lexer" program. In case of a natural language, those categories include nouns, verbs, adjectives, punctuations etc. In case of a programming language, the categories include identifiers, operators, grouping symbols, data types and language keywords. Lexical tokenization is related to the type of tokenization used in large language models (LLMs) but with two differences. First, lexical tokenization is usually based on a lexical grammar, whereas LLM tokenizers are usually probability-based. Second, LLM tokenizers perform a second step that converts the tokens into numerical values. Rule-based programs A rule-based program, performing lexical tokenization, is called ''tokenizer'', or ''scanner'', although ''scanner'' is also a term for the first stage of a lexer. A lexer forms the first phase of a compiler frontend in processing. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Processing
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence. It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics. Major tasks in natural language processing are speech recognition, text classification, natural-language understanding, natural language understanding, and natural language generation. History Natural language processing has its roots in the 1950s. Already in 1950, Alan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is now called the Turing test as a criterion of intelligence, though at the time that was not articulated as a problem separate from artificial intelligence. The proposed test includes a task that involves the automated interpretation and generation of natural language ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
