Co-referential
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Co-referential
In linguistics, coreference, sometimes written co-reference, occurs when two or more expressions refer to the same person or thing; they have the same referent. For example, in ''Bill said Alice would arrive soon, and she did'', the words ''Alice'' and ''she'' refer to the same person. Co-reference is often non-trivial to determine. For example, in ''Bill said he would come'', the word ''he'' may or may not refer to Bill. Determining which expressions are coreferences is an important part of analyzing or understanding the meaning, and often requires information from the context, real-world knowledge, such as tendencies of some names to be associated with particular species ("Rover"), kinds of artifacts ("Titanic"), grammatical genders, or other properties. Linguists commonly use indices to notate coreference, as in ''Billi said hei would come''. Such expressions are said to be ''coindexed'', indicating that they should be interpreted as coreferential. When expressions are corefer ...
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Referent
A referent ( ) is a person or thing to which a name – a linguistic expression or other symbol – refers. For example, in the sentence ''Mary saw me'', the referent of the word ''Mary'' is the particular person called Mary who is being spoken of, while the referent of the word ''me'' is the person uttering the sentence. Two expressions which have the same referent are said to be co-referential. In the sentence ''John had his dog with him'', for instance, the noun ''John'' and the pronoun ''him'' are co-referential, since they both refer to the same person (John). Etymology and meanings The word ''referent'' may be diachronically considered to derive from the Latin ''referentem'', the present participle (in accusative form) of the verb ''referre'' ("carry back", see also etymology of ''refer(ence)''); or synchronically analyzable as the addition of the suffix ''-ent'' to the verb ''refer'' on the model of other English words having that suffix. It is defined in the Merriam-W ...
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Linguistics
Linguistics is the scientific study of language. The areas of linguistic analysis are syntax (rules governing the structure of sentences), semantics (meaning), Morphology (linguistics), morphology (structure of words), phonetics (speech sounds and equivalent gestures in sign languages), phonology (the abstract sound system of a particular language, and analogous systems of sign languages), and pragmatics (how the context of use contributes to meaning). Subdisciplines such as biolinguistics (the study of the biological variables and evolution of language) and psycholinguistics (the study of psychological factors in human language) bridge many of these divisions. Linguistics encompasses Outline of linguistics, many branches and subfields that span both theoretical and practical applications. Theoretical linguistics is concerned with understanding the universal grammar, universal and Philosophy of language#Nature of language, fundamental nature of language and developing a general ...
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Syntactic Relationships
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). Diverse approaches, such as generative grammar and functional grammar, offer unique perspectives on syntax, reflecting its complexity and centrality to understanding human language. Etymology The word ''syntax'' comes from the ancient Greek word , meaning an orderly or systematic arrangement, which consists of (''syn-'', "together" or "alike"), and (''táxis'', "arrangement"). In Hellenistic Greek, this also specifically developed a use referring to the grammatical order of words, with a slightly altered spelling: . The English term, which first appeared in 1548, is partly borrowed from Latin () and Greek, though the Latin ...
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Dan Jurafsky
Daniel Jurafsky is a professor of linguistics and computer science at Stanford University, and also an author. With Daniel Gildea, he is known for developing the first automatic system for semantic role labeling (SRL). He is the author of ''The Language of Food: A Linguist Reads the Menu'' (2014) and a textbook on speech and language processing (2000). For the former, Jurafsky was named a finalist for the James Beard Award. Jurafsky was given a MacArthur Fellowship in 2002. Education Jurafsky received his B.A in linguistics (1983) and Ph.D. in computer science (1992), both at University of California, Berkeley; and then a postdoc at International Computer Science Institute, Berkeley (1992–1995). Academic life He is the author of ''The Language of Food: A Linguist Reads the Menu'' (W. W. Norton & Company, 2014). With James H. Martin, he wrote the textbook ''Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Reco ...
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Neural Network
A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or signal pathways. While individual neurons are simple, many of them together in a network can perform complex tasks. There are two main types of neural networks. *In neuroscience, a '' biological neural network'' is a physical structure found in brains and complex nervous systems – a population of nerve cells connected by synapses. *In machine learning, an '' artificial neural network'' is a mathematical model used to approximate nonlinear functions. Artificial neural networks are used to solve artificial intelligence problems. In biology In the context of biology, a neural network is a population of biological neurons chemically connected to each other by synapses. A given neuron can be connected to hundreds of thousands of synapses. Each neuron sends and receives electrochemical signals called action potentials to its conne ...
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Error Propagation
In statistics, propagation of uncertainty (or propagation of error) is the effect of variables' uncertainties (or errors, more specifically random errors) on the uncertainty of a function based on them. When the variables are the values of experimental measurements they have uncertainties due to measurement limitations (e.g., instrument precision) which propagate due to the combination of variables in the function. The uncertainty ''u'' can be expressed in a number of ways. It may be defined by the absolute error . Uncertainties can also be defined by the relative error , which is usually written as a percentage. Most commonly, the uncertainty on a quantity is quantified in terms of the standard deviation, , which is the positive square root of the variance. The value of a quantity and its error are then expressed as an interval . However, the most general way of characterizing uncertainty is by specifying its probability distribution. If the probability distribution of th ...
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