Contents
Preface............................................................... vii
1 Foundations of non-compositionality.................................
1.1 Background ...................................................
1.2 Lexicographic principles ........................................
1.3 The syntax of definitions ........................................
1.4 The geometry of definitions......................................
1.5 The algebra of definitions .......................................
2 From morphology to syntax ........................................ 23
2.1 Lexical categories and subcategories .............................. 23
2.2 Bound morphemes ............................................. 25
2.3 Relations ..................................................... 30
2.4 Linking....................................................... 39
2.5 Naive grammar ................................................ 46
3 Time and space.................................................... 53
3.1 Space ........................................................ 54
3.2 Time ......................................................... 59
3.3 Indexicals, coercion ............................................ 62
3.4 Measure ...................................................... 65
4 Negation.......................................................... 69
4.1 Negation in the lexicon.......................................... 71
4.2 Quantifiers .................................................... 73
4.3 Negation in compositional constructions ........................... 74
4.4 Double negation ............................................... 77
4.5 Compositional quantifiers ....................................... 78
4.6 Disjunction ................................................... 80
4.7 Scope ambiguities.............................................. 81
4.8 Conclusions ................................................... 82
5 Valuations ........................................................ 83
5.1 Introduction ................................................... 83
5.2 The likeliness scale............................................. 84
5.3 Naive inference (likeliness update) ................................ 86
5.4 Learning...................................................... 89
5.5 Conclusions ................................................... 91
6 Modality ......................................................... 93
6.1 The deontic world .............................................. 93
6.2 Epistemic and autoepistemic logic ................................ 93
6.3 Defaults ...................................................... 93
7 Adjectives, gradience, implicature ................................... 95
7.1 Adjectives .................................................... 95
7.2 Gradience..................................................... 96
7.3 Implicature.................................................... 96
7.4 The elementary pieces .......................................... 97
7.5 The mechanism ................................................ 100
7.6 Memory ...................................................... 103
7.7 Conclusions ................................................... 104
8 Trainability and real-world knowledge............................... 107
8.1 Proper names.................................................. 107
8.2 Trainability ................................................... 109
9 Dynamic
András Kornai is Senior Research Advisor at SZTAKI Institute of Computer Science and full professor at the Department of Algebra, Budapest University of Technology and Economics (BME). He was educated at Eotvos Lorand University (mathematics) and Stanford (linguistics). He wrote the standard textbook Mathematical Linguistics (Springer 2007) and is past president of the Mathematics of Language SIG of ACL. He is author or co-author of over a hundred refereed publications, four monographs (the last one being Semantics, Springer 2019), and five edited volumes. He is senior member of the IEEE, winner of the ACM Distinguished Scientist award, and member of Academia Europaea.
Kornai has broad experience in industrial research (Xerox, IBM, BBN) and at startups (MAD, Calera, Belmont, Northern Light, MetaCarta, MindSpeak) working as chief scientist at the last three. Several of these startups were purchased by industry leaders (Nuance, PPD, Microsoft) and muchof the technology developed under his leadership is still in use. He held various visiting and research positions at Rice University, Boston University, and Harvard. He currently leads the SZTAKI/BME Human Language Technology group.
MindSpeak), working as chief scientist at the last three. Several of these startups were purchased by industry leaders (Nuance, PPD, Microsoft) and much of the technology developed under his leadership is still in use. He held various visiting and research positions at Rice University, Boston University, and Harvard. He currently leads the SZTAKI/BME Human Language Technology group.
MindSpeak), working as chief scientist at the last three. Several of these startups were purchased by industry leaders (Nuance, PPD, Microsoft) and much of the technology developed under his leadership is still in use. He held various visiting and research positions at Rice University, Boston University, and Harvard. He currently leads the SZTAKI/BME Human Language Technology group.
MindSpeak), working as chief scientist at the last three. Several of these startups were purchased by industry leaders (Nuance, PPD, Microsoft) and much of the technology developed under his leadership is still in use. He held various visiting and research positions at Rice University, Boston University, and Harvard. He currently leads the SZTAKI/BME Human Language Technology group
