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DELPH-IN
Deep Linguistic Processing with HPSG - INitiative (DELPH-IN) is a collaboration where computational linguists worldwide develop natural language processing tools for deep linguistic processing of human language. The goal of DELPH-IN is to combine linguistic and statistical processing methods in order to computationally understand the meaning of texts and utterances. The tools developed by DELPH-IN adopt two linguistic formalisms for deep linguistic analysis, viz. head-driven phrase structure grammar (HPSG) and minimal recursion semantics (MRS). All tools under the DELPH-IN collaboration are developed for general use of open-source licensing. Since 2005, DELPH-IN has held an annual summit. This is a loosely structured unconference where people update each other about the work they are doing, seek feedback on current work, and occasionally hammer out agreement on standards and best practice. DELPH-IN technologies and resources The DELPH-IN collaboration has been progressively bu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Head-driven Phrase Structure Grammar
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 ( data type theory and knowledge representation) 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. An HPSG grammar includes principles and grammar rules and lexicon entries which are normally not considered to belong to a grammar. The formalism is based on lexicalism. This means that the lexicon is more than just a list of entries; it is in itself richly structured. Individual entries are marked with types. Types form a hierarchy. Early versions of the grammar were very lexicalized with few grammatical rules (schema). More r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Head-driven Phrase Structure Grammar
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 ( data type theory and knowledge representation) 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. An HPSG grammar includes principles and grammar rules and lexicon entries which are normally not considered to belong to a grammar. The formalism is based on lexicalism. This means that the lexicon is more than just a list of entries; it is in itself richly structured. Individual entries are marked with types. Types form a hierarchy. Early versions of the grammar were very lexicalized with few grammatical rules (schema). More r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
HPSG
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 ( data type theory and knowledge representation) 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. An HPSG grammar includes principles and grammar rules and lexicon entries which are normally not considered to belong to a grammar. The formalism is based on lexicalism. This means that the lexicon is more than just a list of entries; it is in itself richly structured. Individual entries are marked with types. Types form a hierarchy. Early versions of the grammar were very lexicalized with few grammatical rules (schema). More r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Minimal Recursion Semantics
Minimal recursion semantics (MRS) is a framework for computational semantics. It can be implemented in typed feature structure formalisms such as head-driven phrase structure grammar and lexical functional grammar. It is suitable for computational language parsing and natural language generation.Copestake, A., Flickinger, D. P., Sag, I. A., & Pollard, C. (2005)Minimal Recursion Semantics. An introduction In Research on Language and Computation. 3:281–332 MRS enables a simple formulation of the grammatical constraints on lexical and phrasal semantics, including the principles of semantic composition. This technique is used in machine translation. Early pioneers of MRS include Ann Copestake, Dan Flickinger, Carl Pollard, and Ivan Sag Ivan Andrew Sag (November 9, 1949 – September 10, 2013) was an American linguist and cognitive scientist. He did research in areas of syntax and semantics as well as work in computational linguistics. Personal life Born in Alliance, Ohio on N . ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Minimal Recursion Semantics
Minimal recursion semantics (MRS) is a framework for computational semantics. It can be implemented in typed feature structure formalisms such as head-driven phrase structure grammar and lexical functional grammar. It is suitable for computational language parsing and natural language generation.Copestake, A., Flickinger, D. P., Sag, I. A., & Pollard, C. (2005)Minimal Recursion Semantics. An introduction In Research on Language and Computation. 3:281–332 MRS enables a simple formulation of the grammatical constraints on lexical and phrasal semantics, including the principles of semantic composition. This technique is used in machine translation. Early pioneers of MRS include Ann Copestake, Dan Flickinger, Carl Pollard, and Ivan Sag Ivan Andrew Sag (November 9, 1949 – September 10, 2013) was an American linguist and cognitive scientist. He did research in areas of syntax and semantics as well as work in computational linguistics. Personal life Born in Alliance, Ohio on N . ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Minimal Recursion Semantics
Minimal recursion semantics (MRS) is a framework for computational semantics. It can be implemented in typed feature structure formalisms such as head-driven phrase structure grammar and lexical functional grammar. It is suitable for computational language parsing and natural language generation.Copestake, A., Flickinger, D. P., Sag, I. A., & Pollard, C. (2005)Minimal Recursion Semantics. An introduction In Research on Language and Computation. 3:281–332 MRS enables a simple formulation of the grammatical constraints on lexical and phrasal semantics, including the principles of semantic composition. This technique is used in machine translation. Early pioneers of MRS include Ann Copestake, Dan Flickinger, Carl Pollard, and Ivan Sag Ivan Andrew Sag (November 9, 1949 – September 10, 2013) was an American linguist and cognitive scientist. He did research in areas of syntax and semantics as well as work in computational linguistics. Personal life Born in Alliance, Ohio on N . ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Deep Linguistic Processing
Deep linguistic processing is a natural language processing framework which draws on theoretical and descriptive linguistics. It models language predominantly by way of theoretical syntactic/semantic theory (e.g. CCG, HPSG, LFG, TAG, the Prague School). Deep linguistic processing approaches differ from "shallower" methods in that they yield more expressive and structural representations which directly capture long-distance dependencies and underlying predicate-argument structures. The knowledge-intensive approach of deep linguistic processing requires considerable computational power, and has in the past sometimes been judged as being intractable. However, research in the early 2000s had made considerable advancement in efficiency of deep processing. Today, efficiency is no longer a major problem for applications using deep linguistic processing. Contrast to "shallow linguistic processing" Traditionally, deep linguistic processing has been concerned with computational grammar deve ... [...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] |
Parsed Corpus
In linguistics, a treebank is a parsed text corpus that annotated, annotates syntactic or semantic sentence (linguistics), sentence structure. The construction of parsed corpora in the early 1990s revolutionized computational linguistics, which benefitted from large-scale empirical data. Etymology The term ''treebank'' was coined by linguist Geoffrey Leech in the 1980s, by analogy to other repositories such as a seedbank or bloodbank. This is because both syntactic and semantic structure are commonly represented compositionally as a tree structure. The term ''parsed corpus'' is often used interchangeably with the term treebank, with the emphasis on the primacy of sentences rather than trees. Construction Treebanks are often created on top of a corpus that has already been annotated with part-of-speech tagging, part-of-speech tags. In turn, treebanks are sometimes enhanced with semantic or other linguistic information. Treebanks can be created completely manually, where lingu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Treebanks
In linguistics, a treebank is a parsed text corpus that annotates syntactic or semantic sentence structure. The construction of parsed corpora in the early 1990s revolutionized computational linguistics, which benefitted from large-scale empirical data. Etymology The term ''treebank'' was coined by linguist Geoffrey Leech in the 1980s, by analogy to other repositories such as a seedbank or bloodbank. This is because both syntactic and semantic structure are commonly represented compositionally as a tree structure. The term ''parsed corpus'' is often used interchangeably with the term treebank, with the emphasis on the primacy of sentences rather than trees. Construction Treebanks are often created on top of a corpus that has already been annotated with part-of-speech tags. In turn, treebanks are sometimes enhanced with semantic or other linguistic information. Treebanks can be created completely manually, where linguists annotate each sentence with syntactic structure, or ... [...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] |
Shallow Linguistic Processing
Shallow may refer to: Places * Shallow (underwater relief), where the depth of the water is low compared to its surroundings * Shallow Bay (other), various places * Shallow Brook, New Jersey, United States * Shallow Inlet, Victoria, Australia * Shallow Lake, Idaho, United States * Shallow Pond (Plymouth, Massachusetts), United States People * Hyron Shallow (born 1982), West Indian cricketer * Parvati Shallow (born 1982), winner of the reality TV show ''Survivor: Micronesia'' Arts, entertainment, and media * ''Shallow'' (album) * Robert Shallow, a fictional character in two Shakespeare plays * Verbena (band), later known as Shallow Songs * "Shallow" (Lady Gaga and Bradley Cooper song), 2018 * "Shallow" (Porcupine Tree song), 2005 * "The Shallows", a song by Dog's Eye View from the album '' Daisy'' {{disambiguation, geo, surname ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
