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In computational linguistics, coreference resolution is a well-studied problem in discourse. To derive the correct interpretation of a text, or even to estimate the relative importance of various mentioned subjects, pronouns and other referring expressions must be connected to the right individuals. Algorithms intended to resolve coreferences ...
Coreference resolution understands whether multiple words in a text refer to the same entity. It can be useful, for example, to understand the word a pronoun refers to. Consider the following example: Paris is the capital of France. It is also the largest city in France.
It found applications for many natural language processing tasks, such as coreference resolution and polysemy resolution. [5] It is an evolutionary step over ELMo , and spawned the study of "BERTology", which attempts to interpret what is learned by BERT.
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SemEval-2010 – added tasks that were from new areas of studies in computational semantics, viz., Coreference, Ellipsis, Keyphrase Extraction, Noun Compounds and Textual Entailment. SemEval-2012 – co-located with the first *SEM conference and the Semantic Similarity Task was being promoted as the *Sem Shared Task
The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as language detection, tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing and coreference resolution.
resolution sponsors . 110601 (E) The Security Council, Recalling its previous relevant resolutions, including resolution 825 (1993), resolution 1540 (2004), resolution 1695 (2006), and, in particular, resolution 1718 (2006), as well as the statements of its President of 6 October 2006 (S/PRST/2006/41) and 13 April 2009 (S/PRST/2009/7),
In natural language processing a w-shingling is a set of unique shingles (therefore n-grams) each of which is composed of contiguous subsequences of tokens within a document, which can then be used to ascertain the similarity between documents.