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PropBank
PropBank is a corpus that is annotated with verbal propositions and their arguments—a "proposition bank". Although "PropBank" refers to a specific corpus produced by Martha Palmer ''et al.'', the term ''propbank'' is also coming to be used as a common noun referring to any corpus that has been annotated with propositions and their arguments. The PropBank project has played a role in recent research in natural language processing, and has been used in semantic role labelling. Comparison PropBank differs from FrameNet, the resource to which it is most frequently compared, in several ways. PropBank is a verb-oriented resource, while FrameNet is centered on the more abstract notion of frames, which generalizes descriptions across similar verbs (e.g. "describe" and "characterize") as well as nouns and other words (e.g. "description"). PropBank does not annotate events or states of affairs described using nouns. PropBank commits to annotating all verbs in a corpus, whereas the Fr ... [...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 proposed ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Semantic Role Labelling
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 proposed ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
VerbNet
The VerbNet project maps PropBank PropBank is a corpus that is annotated with verbal propositions and their arguments—a "proposition bank". Although "PropBank" refers to a specific corpus produced by Martha Palmer ''et al.'', the term ''propbank'' is also coming to be used a ... verb types to their corresponding Levin classes. It is a lexical resource that incorporates both semantic and syntactic information about its contents. VerbNet is part of thSemLinkproject in development at the University of Colorado. Related projects * UBY a database of 10 resources including VerbNet. External linksKarin Kipper's dissertation— VerbNet: a broad-coverage, comprehensive verb lexicon— contains download of the VerbNet XML files and web interface to the databaseUnified Verb Index— unified index to three lexical semantic resources, VerbNet, PropBank, and FrameNet Lexical databases Corpora {{corpora-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
FrameNet
FrameNet is a research and resource development project based at the International Computer Science Institute (ICSI) in Berkeley, California, which has produced an electronic resource based on a theory of meaning called frame semantics. The data that FrameNet has analyzed show that the sentence "John sold a car to Mary" essentially describes the same basic situation (semantic frame) as "Mary bought a car from John", just from a different perspective. A semantic frame is a conceptual structure describing an event, relation, or object along with its participants. The FrameNet lexical database contains over 1,200 semantic ''frames'', 13,000 ''lexical units'' (a pairing of a word with a meaning; polysemous words are represented by several ''lexical units'') and 202,000 example sentences. Charles J. Fillmore, who developed the theory of frame semantics which serves as the theoretical the basis of FrameNet, founded the project in 1997 and continued to lead the effort until he died in 2 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Text Corpus
In linguistics, a corpus (plural ''corpora'') or text corpus is a language resource consisting of a large and structured set of texts (nowadays usually electronically stored and processed). In corpus linguistics, they are used to do statistical analysis and statistical hypothesis testing, hypothesis testing, checking occurrences or validating linguistic rules within a specific language territory. In Search engine (computing), search technology, a corpus is the collection of documents which is being searched. Overview A corpus may contain texts in a single language (''monolingual corpus'') or text data in multiple languages (''multilingual corpus''). In order to make the corpora more useful for doing linguistic research, they are often subjected to a process known as annotation. An example of annotating a corpus is part-of-speech tagging, or ''POS-tagging'', in which information about each word's part of speech (verb, noun, adjective, etc.) is added to the corpus in the form o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Annotation
An annotation is extra information associated with a particular point in a document or other piece of information. It can be a note that includes a comment or explanation. Annotations are sometimes presented in the margin of book pages. For annotations of different digital media, see web annotation and text annotation. Literature and education Textual scholarship Textual scholarship is a discipline that often uses the technique of annotation to describe or add additional historical context to texts and physical documents to make it easier to understand. Student uses Students often highlight passages in books in order to refer back to key phrases easily, or add marginalia to aid studying. Annotated bibliographies add commentary on the relevance or quality of each source, in addition to the usual bibliographic information that merely identifies the source. Mathematical expression annotation Mathematical expressions (symbols and formulae) can be annotated with their natural ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Proposition
In logic and linguistics, a proposition is the meaning of a declarative sentence. In philosophy, " meaning" is understood to be a non-linguistic entity which is shared by all sentences with the same meaning. Equivalently, a proposition is the non-linguistic bearer of truth or falsity which makes any sentence that expresses it either true or false. While the term "proposition" may sometimes be used in everyday language to refer to a linguistic statement which can be either true or false, the technical philosophical term, which differs from the mathematical usage, refers exclusively to the non-linguistic meaning behind the statement. The term is often used very broadly and can also refer to various related concepts, both in the history of philosophy and in contemporary analytic philosophy. It can generally be used to refer to some or all of the following: The primary bearers of truth values (such as "true" and "false"); the objects of belief and other propositional attitudes (i.e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Common Noun
A proper noun is a noun that identifies a single entity and is used to refer to that entity (''Africa'', ''Jupiter'', ''Sarah'', ''Microsoft)'' as distinguished from a common noun, which is a noun that refers to a class of entities (''continent, planet, person, corporation'') and may be used when referring to instances of a specific class (a ''continent'', another ''planet'', these ''persons'', our ''corporation''). Some proper nouns occur in plural form (optionally or exclusively), and then they refer to ''groups'' of entities considered as unique (the ''Hendersons'', the ''Everglades'', ''the Azores'', the ''Pleiades''). Proper nouns can also occur in secondary applications, for example modifying nouns (the ''Mozart'' experience; his ''Azores'' adventure), or in the role of common nouns (he's no ''Pavarotti''; a few would-be ''Napoleons''). The detailed definition of the term is problematic and, to an extent, governed by convention. A distinction is normally made in current ling ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Processing
Natural language processing (NLP) is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves. Challenges in natural language processing frequently involve speech recognition, 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, t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Constituent (linguistics)
In syntactic analysis, a constituent is a word or a group of words that function as a single unit within a hierarchical structure. The constituent structure of sentences is identified using ''tests for constituents''. These tests apply to a portion of a sentence, and the results provide evidence about the constituent structure of the sentence. Many constituents are phrases. A phrase is a sequence of one or more words (in some theories two or more) built around a head lexical item and working as a unit within a sentence. A word sequence is shown to be a phrase/constituent if it exhibits one or more of the behaviors discussed below. The analysis of constituent structure is associated mainly with phrase structure grammars, although dependency grammars also allow sentence structure to be broken down into constituent parts. Tests for constituents in English Tests for constituents are diagnostics used to identify sentence structure. There are numerous tests for constituents that are co ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computational Linguistics
Computational linguistics is an Interdisciplinarity, interdisciplinary field concerned with the computational modelling of natural language, as well as the study of appropriate computational approaches to linguistic questions. In general, computational linguistics draws upon linguistics, computer science, artificial intelligence, mathematics, logic, philosophy, cognitive science, cognitive psychology, psycholinguistics, anthropology and neuroscience, among others. Sub-fields and related areas Traditionally, computational linguistics emerged as an area of artificial intelligence performed by computer scientists who had specialized in the application of computers to the processing of a natural language. With the formation of the Association for Computational Linguistics (ACL) and the establishment of independent conference series, the field consolidated during the 1970s and 1980s. The Association for Computational Linguistics defines computational linguistics as: The term "comp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
