In linguistics, syntax is the study of how words and morphemes combine to form larger units such as phrases and sentences. Central concerns of syntax include word order, grammatical relations, hierarchical sentence structure (constituency), agreement, the nature of crosslinguistic variation, and the relationship between form and meaning (semantics). There are numerous approaches to syntax that differ in their central assumptions and goals.
WordNet is a lexical database of semantic relations between words that links words into semantic relations including synonyms, hyponyms, and meronyms. The synonyms are grouped into synsets with short definitions and usage examples. It can thus be seen as a combination and extension of a dictionary and thesaurus. While it is accessible to human users via a web browser, its primary use is in automatic text analysis and artificial intelligence applications. It was first created in the English language and the English WordNet database and software tools have been released under a BSD style license and are freely available for download from that WordNet website. There are now WordNets in more than 200 languages.
Word-sense disambiguation (WSD) is the process of identifying which sense of a word is meant in a sentence or other segment of context. In human language processing and cognition, it is usually subconscious/automatic, but can often come to conscious attention when ambiguity impairs clarity of communication, given the pervasive polysemy in natural language. In computational linguistics, it is an open problem that affects other computer-related writing, such as discourse, improving relevance of search engines, anaphora resolution, coherence, and inference.
Head-driven phrase structure grammar (HPSG) is a highly lexicalized, constraint-based grammar developed by Carl Pollard and Ivan Sag. It is a type of phrase structure grammar, as opposed to a dependency grammar, and it is the immediate successor to generalized phrase structure grammar. HPSG draws from other fields such as computer science and uses Ferdinand de Saussure's notion of the sign. It uses a uniform formalism and is organized in a modular way which makes it attractive for natural language processing.
Tree-adjoining grammar (TAG) is a grammar formalism defined by Aravind Joshi. Tree-adjoining grammars are somewhat similar to context-free grammars, but the elementary unit of rewriting is the tree rather than the symbol. Whereas context-free grammars have rules for rewriting symbols as strings of other symbols, tree-adjoining grammars have rules for rewriting the nodes of trees as other trees.
Generalized phrase structure grammar (GPSG) is a framework for describing the syntax and semantics of natural languages. It is a type of constraint-based phrase structure grammar. Constraint based grammars are based around defining certain syntactic processes as ungrammatical for a given language and assuming everything not thus dismissed is grammatical within that language. Phrase structure grammars base their framework on constituency relationships, seeing the words in a sentence as ranked, with some words dominating the others. For example, in the sentence "The dog runs", "runs" is seen as dominating "dog" since it is the main focus of the sentence. This view stands in contrast to dependency grammars, which base their assumed structure on the relationship between a single word in a sentence and its dependents.
A symbolic linguistic representation is a representation of an utterance that uses symbols to represent linguistic information about the utterance, such as information about phonetics, phonology, morphology, syntax, or semantics. Symbolic linguistic representations are different from non-symbolic representations, such as recordings, because they use symbols to represent linguistic information rather than measurements.
Semantic similarity is a metric defined over a set of documents or terms, where the idea of distance between items is based on the likeness of their meaning or semantic content as opposed to lexicographical similarity. These are mathematical tools used to estimate the strength of the semantic relationship between units of language, concepts or instances, through a numerical description obtained according to the comparison of information supporting their meaning or describing their nature. The term semantic similarity is often confused with semantic relatedness. Semantic relatedness includes any relation between two terms, while semantic similarity only includes "is a" relations. For example, "car" is similar to "bus", but is also related to "road" and "driving".
Gerald James Michael Gazdar, FBA is a British linguist and computer scientist.
Frame semantics is a theory of linguistic meaning developed by Charles J. Fillmore that extends his earlier case grammar. It relates linguistic semantics to encyclopedic knowledge. The basic idea is that one cannot understand the meaning of a single word without access to all the essential knowledge that relates to that word. For example, one would not be able to understand the word "sell" without knowing anything about the situation of commercial transfer, which also involves, among other things, a seller, a buyer, goods, money, the relation between the money and the goods, the relations between the seller and the goods and the money, the relation between the buyer and the goods and the money and so on. Thus, a word activates, or evokes, a frame of semantic knowledge relating to the specific concept to which it refers.
Distributional semantics is a research area that develops and studies theories and methods for quantifying and categorizing semantic similarities between linguistic items based on their distributional properties in large samples of language data. The basic idea of distributional semantics can be summed up in the so-called distributional hypothesis: linguistic items with similar distributions have similar meanings.
Generative lexicon (GL) is a theory of linguistic semantics which focuses on the distributed nature of compositionality in natural language. The first major work outlining the framework is James Pustejovsky's 1991 article "The Generative Lexicon". Subsequent important developments are presented in Pustejovsky and Boguraev (1993), Bouillon (1997), and Busa (1996). The first unified treatment of GL was given in Pustejovsky (1995). Unlike purely verb-based approaches to compositionality, generative lexicon attempts to spread the semantic load across all constituents of the utterance. Central to the philosophical perspective of GL are two major lines of inquiry: (1) How is it that we are able to deploy a finite number of words in our language in an unbounded number of contexts? (2) Is lexical information and the representations used in composing meanings separable from our commonsense knowledge?
Meaning–text theory (MTT) is a theoretical linguistic framework, first put forward in Moscow by Aleksandr Žolkovskij and Igor Mel’čuk, for the construction of models of natural language. The theory provides a large and elaborate basis for linguistic description and, due to its formal character, lends itself particularly well to computer applications, including machine translation, phraseology, and lexicography.
Quantitative comparative linguistics is the use of quantitative analysis as applied to comparative linguistics. Examples include the statistical fields of lexicostatistics and glottochronology, and the borrowing of phylogenetics from biology.
Linguistics is the scientific study of language. Linguistics is based on a theoretical as well as a descriptive study of language and is also interlinked with the applied fields of language studies and language learning, which entails the study of specific languages. Before the 20th century, linguistics evolved in conjunction with literary study and did not employ scientific methods. Modern-day linguistics is considered a science because it entails a comprehensive, systematic, objective, and precise analysis of all aspects of language – i.e., the cognitive, the social, the cultural, the psychological, the environmental, the biological, the literary, the grammatical, the paleographical, and the structural.
BabelNet is a multilingual lexicalized semantic network and ontology developed at the NLP group of the Sapienza University of Rome. BabelNet was automatically created by linking Wikipedia to the most popular computational lexicon of the English language, WordNet. The integration is done using an automatic mapping and by filling in lexical gaps in resource-poor languages by using statistical machine translation. The result is an encyclopedic dictionary that provides concepts and named entities lexicalized in many languages and connected with large amounts of semantic relations. Additional lexicalizations and definitions are added by linking to free-license wordnets, OmegaWiki, the English Wiktionary, Wikidata, FrameNet, VerbNet and others. Similarly to WordNet, BabelNet groups words in different languages into sets of synonyms, called Babel synsets. For each Babel synset, BabelNet provides short definitions in many languages harvested from both WordNet and Wikipedia.
In natural language processing (NLP), a word embedding is a representation of a word. The embedding is used in text analysis. Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. Word embeddings can be obtained using language modeling and feature learning techniques, where words or phrases from the vocabulary are mapped to vectors of real numbers.
Ann Alicia Copestake is professor of computational linguistics and head of the Department of Computer Science and Technology at the University of Cambridge and a fellow of Wolfson College, Cambridge.
Dynamic Syntax (DS) is a grammar formalism and linguistic theory whose overall aim is to explain the real-time processes of language understanding and production, and describe linguistic structures as happening step-by-step over time. Under the DS approach, syntactic knowledge is understood as the ability to incrementally analyse the structure and content of spoken and written language in context and in real-time. While it posits representations similar to those used in Combinatory categorial grammars (CCG), it builds those representations left-to-right going word-by-word. Thus it differs from other syntactic models which generally abstract away from features of everyday conversation such as interruption, backtracking, and self-correction. Moreover, it differs from other approaches in that it does not postulate an independent level of syntactic structure over words.
In natural language processing, linguistics, and neighboring fields, Linguistic Linked Open Data (LLOD) describes a method and an interdisciplinary community concerned with creating, sharing, and (re-)using language resources in accordance with Linked Data principles. The Linguistic Linked Open Data Cloud was conceived and is being maintained by the Open Linguistics Working Group (OWLG) of the Open Knowledge Foundation, but has been a point of focal activity for several W3C community groups, research projects, and infrastructure efforts since then.
