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The output of a word-sense induction algorithm is a clustering of contexts in which the target word occurs or a clustering of words related to the target word. Three main methods have been proposed in the literature: [1] [2] Context clustering; Word clustering; Co-occurrence graphs
Given the difficulties of identifying word senses, other tasks relevant to this topic include word-sense induction, subcategorization acquisition, and evaluation of lexical resources. The second major area in semantic analysis is the understanding of how different sentence and textual elements fit together.
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.
The American Heritage Dictionary of the English Language, Third Edition In the introduction to the 4th and 5th editions, it is mentioned that more than 10,000 words have been added, thus the total for the 5th edition will be more than 370,000 words. [28] [failed verification] Finnish: 350,000
word-sense induction – the task of automatically acquiring the senses of a target word; word-sense disambiguation – the task of automatically associating a sense with a word in context; lexical substitution – the task of replacing a word in context with a lexical substitute; sememe – unit of meaning; linguistics – the scientific study ...
WSD exercises require a dictionary, to specify the word senses which are to be disambiguated, and a corpus of language data to be disambiguated. WordNet is the most popular example of sense inventory. The reason for adopting the HECTOR database during Senseval-1 was that the WordNet inventory was already publicly available. [2]
Oversupply would rise to 1.4 million barrels per day in 2025 if OPEC+ follows through on plans to unwind quotas in April, the IEA said. Even if production cuts stay in place through all of next ...
for every sense of the word being disambiguated one should count the number of words that are in both the neighborhood of that word and in the dictionary definition of that sense; the sense that is to be chosen is the sense that has the largest number of this count. A frequently used example illustrating this algorithm is for the context "pine ...
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