Semantic Relations in Diachronic Word Families

Talk, held at the 6th Indo-European Research Colloquium (Jena/Cologne, 2022/03/07).

Transcript

1. LC CA Semantic Relations in Diachronic Word Families Nathanael E. Schweikhard Max Planck Institutes for Evolutionary Anthropology and Science of Human History Department of Linguistic and Cultural Evolution Project CALC March 7, 2022 1 / 23
2. Table of Contents 1 Semantic Relations 2 Materials and Methods 3 Results 4 Mechanisms of Language Change 5 Conclusion 2 / 23
3. Semantic Relations ungelücke ‘bad fortune’ gelücke ‘good or bad fortune’ glück ‘good fortune’ Glück ‘good fortune, happiness’ derivation sound change sound change semantic change semantic difference formal relations semantic relations Unglück ‘bad fortune’ sound change semantic change 3 / 23
4. Semantic Relations arzāt ‘physician’ arciater 'senior physician' borrowing semantic difference formal relations semantic relations Arzt ‘physician’ sound change 4 / 23
5. Semantic Relations (Koch 2001, Pepper and Arnaud 2020) Semantic Relations identity BOW composition WOOD possession ARCHER ... ... production BOWYER metaphor ELBOW hyponymy LONGBOW hyperonymy WEAPON similarity contrast taxonomy contiguity containment causation co-taxonymy CROSSBOW 5 / 23
6. Semantic Relations (Koch 2001, Pepper and Arnaud 2020) Semantic Relations identity BOW similarity contrast contiguity 6 / 23
7. Semantic Relations (Koch 2001, Pepper and Arnaud 2020) HIGH -> HEIGHT Semantic Relations identity BOW similarity contrast contiguity 7 / 23
8. Semantic Relations (Koch 2001, Pepper and Arnaud 2020) FORTUNE -> MISFORTUNE HIGH -> HEIGHT Semantic Relations identity BOW similarity contrast contiguity 8 / 23
9. Semantic Relations (Koch 2001, Pepper and Arnaud 2020) composition WOOD possession ARCHER ... ... production BOWYER containment causation Semantic Relations identity BOW similarity contrast contiguity 9 / 23
10. Semantic Relations (Koch 2001, Pepper and Arnaud 2020) Semantic Relations identity BOW composition WOOD possession ARCHER ... ... production BOWYER metaphor ELBOW hyponymy LONGBOW hyperonymy WEAPON similarity contrast taxonomy contiguity containment causation co-taxonymy CROSSBOW 10 / 23
11. Materials 480 German nouns basic vocabulary from NorthEuraLex etymological information from Kroonen 2013 Pfeifer et al. 1993 11 / 23
12. Method of Data Annotation ID SOURCE FORM SOURCE CONCEPT SOURCE PROCESS SEMANTIC RELATION ID TARGET FORM TARGET CONCEPT TARGET 1 gelücke good or bad fortune sound change taxonomy 2 glück good fortune 2 glück good fortune sound change contiguity 3 Glück happiness 1 gelücke good or bad fortune derivation taxonomy 4 ungelücke bad fortune 4 ungelücke bad fortune sound change unchanged inheritance 5 Unglück bad luck 12 / 23
13. Influence of Reconstruction identity (4.6%) taxonomy (42.0%) metaphor (13.0%) contiguity (38.9%) attested (N = 131) loan (1.5%) identity (17.6%) taxonomy (24.7%) metaphor (24.7%) contiguity (32.9%) reconstructed(N=85) 13 / 23
14. Influence of Part of Speech identity (4.6%) taxonomy (42.0%) metaphor (13.0%) contiguity (38.9%) loan (1.5%) identity (39.1%) metaphor (8.7%) contiguity (52.2%) identity (15.4%) contiguity (84.6%) Noun -> Noun (N=131) Adjective -> Noun (N=26) Verb -> Noun (N=23) 14 / 23
15. Influence of Part of Speech (only word formation) identity (39.1%) metaphor (8.7%) contiguity (52.2%) identity (15.4%) contiguity (84.6%) Noun -> Noun (N=63) Adjective -> Noun (N=26) Verb -> Noun (N=23) taxonomy (34.9%) identity (9.5%) contiguity (42.9%) metaphor (12.7%) 15 / 23
16. Influence of Type of Process word formation (N=57) hyperonymy (5.3%) hyponymy (31.6%) co-taxonomy (1.8%) containment (33.3%) causation (14.0%) hyperonymy (5.3%) hyponymy (31.6%) containment (33.3%) causation (14.0%) metaphor (14.0%) taxonomy (38.6%) contiguity (47.4%) semantic change (N=55) borrowing (N=13) hyperonymy (29.1%) hyponymy (16.4%) containment (14.5%) causation (23.6%) loan (3.6%) contiguity (38.2%) taxonomy (45.5%) metaphor (12.7%) hyperonymy (38.5%) hyponymy (23.1%) containment (23.1%) taxonomy (61.5%) contiguity (23.1%) metaphor (15.4%) 16 / 23
17. Influence of Type of Word Formation derivation (N=17) hyperonymy (17.6%) hyponymy (23.5%) co-taxonomy (5.9%) containment (41.2%) causation (11.8%) contiguity (52.9%) taxonomy (47.1%) compound modifiers (N=15) compound heads (N=25) containment (66.7%) causation (33.3%) contiguity (100.0%) hyponymy (56.0%) containment (8.0%) causation (4.0%) metaphor (32.0%) contiguity (12.0%) taxonomy (56.0%) 17 / 23
18. Influence of Semantic Field borrowing 11.2 % compounding derivation 10.6 % objects (N=329) animals (N=39) body parts (N=48) persons (N=33) time (N=31) borrowing 0 % compounding 2.7 % derivation 7.7 % borrowing 6.3 % compounding 8.3 % derivation 0 % borrowing 18.2 % compounding 12.1 % derivation 3.0 % borrowing 41.9 % compounding 22.6 % derivation 3.2 % 1.8 % 18 / 23
19. Mechanisms of Language Change (Enfield 2015, Koch 2016) process type word formation hearer semantic change speaker borrowing innovation by 19 / 23
20. Influence of Type of Word Formation derivation (N=17) hyperonymy (17.6%) hyponymy (23.5%) co-taxonomy (5.9%) containment (41.2%) causation (11.8%) contiguity (52.9%) taxonomy (47.1%) compound modifiers (N=15) compound heads (N=25) containment (66.7%) causation (33.3%) contiguity (100.0%) hyponymy (56.0%) containment (8.0%) causation (4.0%) metaphor (32.0%) contiguity (12.0%) taxonomy (56.0%) 20 / 23
21. Influence of Type of Process word formation (N=57) hyperonymy (5.3%) hyponymy (31.6%) co-taxonomy (1.8%) containment (33.3%) causation (14.0%) hyperonymy (5.3%) hyponymy (31.6%) containment (33.3%) causation (14.0%) metaphor (14.0%) taxonomy (38.6%) contiguity (47.4%) semantic change (N=55) borrowing (N=13) hyperonymy (29.1%) hyponymy (16.4%) containment (14.5%) causation (23.6%) loan (3.6%) contiguity (38.2%) taxonomy (45.5%) metaphor (12.7%) hyperonymy (38.5%) hyponymy (23.1%) containment (23.1%) taxonomy (61.5%) contiguity (23.1%) metaphor (15.4%) 21 / 23
22. Conclusion connection between method of innovation and semantic relation contiguity overall most important semantic relation taxonomy predominant in hearer-based innovations many other factors involved more data needed 22 / 23
23. Thank You! Thank you very much for your attention! 23 / 23