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This paper is a reflexion on the computability of natural language semantics. It does not contain a new model or new results in the formal semantics of natural language: it is rather a computational analysis of the logical models and algorithms currently used in natural language semantics, defined as the mapping of a statement to logical formulas - formulas, because a statement can be ambiguous. We argue that as long as possible world semantics is left out, one can compute the semantic representation(s) of a given statement, including aspects of lexical meaning. We also discuss the algorithmic complexity of this process.
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, Computability, Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Natural language processing, Complexity, Computational Complexity (cs.CC), Formal semantics, Computer Science - Computational Complexity, Artificial Intelligence (cs.AI), [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], Categorial grammar, [INFO.INFO-CC] Computer Science [cs]/Computational Complexity [cs.CC], Computation and Language (cs.CL)
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, Computability, Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Natural language processing, Complexity, Computational Complexity (cs.CC), Formal semantics, Computer Science - Computational Complexity, Artificial Intelligence (cs.AI), [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL], Categorial grammar, [INFO.INFO-CC] Computer Science [cs]/Computational Complexity [cs.CC], Computation and Language (cs.CL)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |