Abstract
Barsalou (1992), Löbner (2014, 2015) hypothesise that frames form the natural way in which the brain represents concepts and more complicated semantic content built from concepts. An interesting aspect of the hypothesis is that it becomes easy to define stochastic properties of concepts. Particular frames can be seen as a collection of stochastic variables.
This paper develops a simple but powerful notion of semantic memory on the basis of an earlier concept of lexical knowledge under the frame hypothesis. It then tries to answer the question of whether the stochastic information in semantic memory contributes to conceptual content.
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Notes
- 1.
- 2.
See Petersen (2007) for the motivation for central nodes.
- 3.
Frame semantics as presented here can be seen as a more structured version of DRT in which frames are both discourse markers (their referential function) and conditions (seeing them as formulas).
- 4.
Such corpora do not currently exist and their construction would require considerable annotation effort. The construction of f is also non-trivial since frames —at this point not an improvement from logical formulas— do not have a unique decomposition. One would need —for the attribution of specific subframes to words— to see what generalises best over different uses of the same word. It should be possible in this way to obtain a full semantic lexicon from just a pairing of utterances and their frame-semantic meaning representation.
- 5.
Jones et al. (2015) is a good overview.
- 6.
The importance of diagnosticity for natural concepts is stressed by Annika Schuster in ongoing work.
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Zeevat, H. (2019). From Semantic Memory to Semantic Content. In: Silva, A., Staton, S., Sutton, P., Umbach, C. (eds) Language, Logic, and Computation. TbiLLC 2018. Lecture Notes in Computer Science(), vol 11456. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-59565-7_16
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