Roberto Navigli
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Roberto Navigli
Roberto Navigli (born 1978) is an Italian computer scientist and professor in the Department of Computer, Control and Management Engineering "Antonio Ruberti" at the Sapienza University of Rome, where he is also the director of the Sapienza NLP Group. Education Navigli obtained his Master of Science degree in Computer Science in 2001 at Sapienza University of Rome, followed, in 2007, by a PhD from the same institution, under the supervision of Paola Velardi. Navigli's doctoral thesis focused on devising and evaluating an innovative knowledge-based algorithm for Word Sense Disambiguation, named Structural Semantic Interconnections. Career and research Navigli's research focuses on Artificial Intelligence, specifically on enabling computers to understand and represent meaning across hundreds of languages, making significant contributions to various fields within Natural Language Processing, including Word Sense Disambiguation, Entity Linking, Semantic Role Labeling and sema ...
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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 ...
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Word Sense Disambiguation
Word-sense disambiguation 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. Given that natural language requires reflection of neurological reality, as shaped by the abilities provided by the brain's neural networks, computer science has had a long-term challenge in developing the ability in computers to do natural language processing and machine learning. Many techniques have been researched, including dictionary-based methods that use the knowledge encoded in lexical resources, supervised machine learning methods in which a classifier is trained for each distinct word on a corpus of manually sense-annotated examples, and completely unsupervised methods that cluster occurrences of words, thereby inducing word senses. Among these, supervised learning approaches have been the most successful algorithms to date. Accuracy of current algorithms is dif ...
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Time (magazine)
''Time'' (stylized in all caps as ''TIME'') is an American news magazine based in New York City. It was published Weekly newspaper, weekly for nearly a century. Starting in March 2020, it transitioned to every other week. It was first published in New York City on March 3, 1923, and for many years it was run by its influential co-founder, Henry Luce. A European edition (''Time Europe'', formerly known as ''Time Atlantic'') is published in London and also covers the Middle East, Africa, and, since 2003, Latin America. An Asian edition (''Time Asia'') is based in Hong Kong. The South Pacific edition, which covers Australia, New Zealand, and the Pacific Islands, is based in Sydney. Since 2018, ''Time'' has been owned by Salesforce founder Marc Benioff, who acquired it from Meredith Corporation. Benioff currently publishes the magazine through the company Time USA, LLC. History 20th century ''Time'' has been based in New York City since its first issue published on March 3, 1923 ...
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Wikidata
Wikidata is a collaboratively edited multilingual knowledge graph hosted by the Wikimedia Foundation. It is a common source of open data that Wikimedia projects such as Wikipedia, and anyone else, are able to use under the CC0 public domain license. Wikidata is a wiki powered by the software MediaWiki, including its extension for semi-structured data, the Wikibase. As of early 2025, Wikidata had 1.65 billion item statements ( semantic triples). Concept Wikidata is a document-oriented database, focusing on ''items'', which represent any kind of topic, concept, or object. Each item is allocated a unique persistent identifier called its ''QID'', a positive integer prefixed with the upper-case letter "Q". This makes it possible to provide translations of the basic information describing the topic each item covers without favouring any particular language. Some examples of items and their QIDs are , , , , and . Item ''labels'' do not need to be unique. For example, th ...
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Wiktionary
Wiktionary (, ; , ; rhyming with "dictionary") is a multilingual, web-based project to create a free content dictionary of terms (including words, phrases, proverbs, linguistic reconstructions, etc.) in all natural languages and in a number of artificial languages. These entries may contain definitions, images for illustration, pronunciations, etymologies, inflections, usage examples, quotations, related terms, and translations of terms into other languages, among other features. It is collaboratively edited via a wiki. Its name is a portmanteau of the words ''wiki'' and ''dictionary''. It is available in languages and in Simple English. Like its sister project Wikipedia, Wiktionary is run by the Wikimedia Foundation, and is written collaboratively by volunteers, dubbed "Wiktionarians". Its wiki software, MediaWiki, allows almost anyone with access to the website to create and edit entries. Because Wiktionary is not limited by print space considerations, most of Wiktiona ...
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Wikipedia
Wikipedia is a free content, free Online content, online encyclopedia that is written and maintained by a community of volunteers, known as Wikipedians, through open collaboration and the wiki software MediaWiki. Founded by Jimmy Wales and Larry Sanger in 2001, Wikipedia has been hosted since 2003 by the Wikimedia Foundation, an American 501(c)(3) organization, nonprofit organization funded mainly by donations from readers. Wikipedia is the largest and most-read reference work in history. Initially available only in English language, English, Wikipedia exists list of Wikipedias, in over 340 languages. The English Wikipedia, with over  million Article (publishing), articles, remains the largest of the editions, which together comprise more than articles and attract more than 1.5 billion unique device visits and 13 million edits per month (about 5edits per second on average) . , over 25% of Wikipedia's web traffic, traffic comes from the United States, while Jap ...
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WordNet
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. Its primary use is in automatic natural language processing, 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 License, BSD style license and are freely available for download. The latest official release from Princeton was released in 2011. Princeton currently has no plans to release any new versions due to staffing and funding issues. New versions are still being released annually through the Open English WordNet website. Until about 2024 an online version was previously available through wordnet.princeton.edu. That version of WordNet h ...
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Knowledge Graph
In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a Graph (discrete mathematics), graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of Named entity, entities objects, events, situations or abstract concepts while also encoding the free-form semantics or relationships underlying these entities. Since the development of the Semantic Web, knowledge graphs have often been associated with linked data, linked open data projects, focusing on the connections between concepts and entities. They are also historically associated with and used by search engines such as Google Knowledge Graph, Google, Bing (search engine), Bing, Yext and Yahoo; Knowledge Engine (Wikimedia Foundation), knowledge-engines and question-answering services such as WolframAlpha, Apple's Siri, and Amazon Amazon Alexa, Alexa; and social networks such as LinkedIn and Facebook. Recent deve ...
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European Research Council
The European Research Council (ERC) is a public body for funding of scientific and technological research conducted within the European Union (EU). Established by the European Commission in 2007, the ERC is composed of an independent Scientific Council, its governing body consisting of distinguished researchers, and an Executive Agency, in charge of the implementation. It forms part of the framework programme of the union dedicated to research and innovation, Horizon 2020, preceded by the Seventh Research Framework Programme (FP7). The ERC budget is over €13 billion from 2014 – 2020 and comes from the Horizon 2020 programme, a part of the European Union's budget. Under Horizon 2020 it is estimated that around 7,000 ERC grantees will be funded and 42,000 team members supported, including 11,000 doctoral students and almost 16,000 post-doctoral researchers. The ERC awards to individuals are widely considered to be either among the most, or else the most prestigious grant for aca ...
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Semantic Parsing
Semantic parsing is the task of converting a natural language utterance to a logical form: a machine-understandable representation of its meaning. Semantic parsing can thus be understood as extracting the precise meaning of an utterance. Applications of semantic parsing include machine translation, question answering,Berant, Jonathan, et al"Semantic Parsing on Freebase from Question-Answer Pairs."EMNLP. Vol. 2. No. 5. 2013. ontology induction, automated reasoning, and code generation. The phrase was first used in the 1970s by Yorick Wilks as the basis for machine translation programs working with only semantic representations. Semantic parsing is one of the important tasks in computational linguistics and natural language processing. Semantic parsing maps text to formal meaning representations. This contrasts with semantic role labeling and other forms of shallow semantic processing, which do not aim to produce complete formal meanings. In computer vision, semantic parsing ...
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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 ...
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Entity Linking
In natural language processing, Entity Linking, also referred to as named-entity disambiguation (NED), named-entity recognition and disambiguation (NERD), named-entity normalization (NEN), or Concept Recognition, is the task of assigning a unique identity to entities (such as famous individuals, locations, or companies) mentioned in text. For example, given the sentence ''"Paris is the capital of France"'', the main idea is to first identify ''"Paris"'' and ''"France"'' as named entities, and then to determine that ''"Paris"'' refers to the city of Paris and not to Paris Hilton or any other entity that could be referred to as ''"Paris"'' and ''"France"'' to the french country. The Entity Linking task is composed of 3 subtasks. # Named Entity Recognition: Extraction of named entities from a text. # Candidate Generation: For each named entity, select possible candidates from a Knowledge Base (e.g. Wikipedia, Wikidata, DBPedia, ...). # Disambiguation: Choose the correct entit ...
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