Understanding Textual Entailment in Natural Language Processing

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This collection of images showcases various aspects of textual entailment, where one text can entail another. It explores the relationship between statements like "muscles move bones" and "muscles generate movement". Different levels of entailment are depicted, culminating in complete textual entailment examples. The images depict scenarios where the statement "the muscles' main job is to move bones" can be fully or partially entailed by related statements.


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  1. Recognizing Partial Textual Entailment Omer Levy Natural Language Processing Lab Bar-Ilan University Ido Dagan Torsten Zesch Ubiquitous Knowledge Processing Lab Technische Universit t Darmstadt Iryna Gurevych 1

  2. Textual Entailment 2

  3. T: muscles move bones 3

  4. T: muscles move bones H: muscles generate movement 4

  5. T: muscles move bones H: muscles generate movement 5

  6. T: muscles move bones ? H: the muscles main job is to move bones 6

  7. T: muscles move bones H: the muscles main job is to move bones 7

  8. Complete Textual Entailment 8

  9. Complete Textual Entailment 9

  10. Complete Textual Entailment . Partial . 10

  11. Complete Textual Entailment . Partial . (Nielsen et al, 2009) 11

  12. T: muscles move bones H: the muscles main job is to move bones 12

  13. T: muscles move bones (main job of muscles) (muscles move) (bones are moved) H: the muscles main job is to move bones 13

  14. T: muscles move bones (main job of muscles) (muscles move) (bones are moved) H: the muscles main job is to move bones 14

  15. T: muscles move bones (main job of muscles) (muscles move) (bones are moved) H: the muscles main job is to move bones 15

  16. T: muscles move bones (main job of muscles) (muscles move) (bones are moved) H: the muscles main job is to move bones 16

  17. Facets T: muscles move bones (main job of muscles) (muscles move) (bones are moved) H: the muscles main job is to move bones 17

  18. Facets T: muscles move bones (main job of muscles) (muscles move) (bones are moved) H: the muscles main job is to move bones (main job, muscles) (muscles, move) (move, bones) 18

  19. Facets T: muscles move bones (main job of muscles) (muscles move) (bones are moved) H: the muscles main job is to move bones (main job, muscles) (muscles, move) (move, bones) 19

  20. Facets T: muscles move bones (main job of muscles) (muscles move) (bones are moved) H: the muscles main job is to move bones (main job, muscles) (muscles, move) (move, bones) 20

  21. Facet: a pair of terms and their implied semantic relation. 21

  22. (move, bones) Facet: a pair of terms and their implied semantic relation. 22

  23. (move, bones) Facet: a pair of terms and their implied semantic relation. theme is to move bones 23

  24. Recognizing Faceted Entailment 24

  25. Recognizing Faceted Entailment T: muscles move bones H: the muscles main job is to move bones 25

  26. Recognizing Faceted Entailment T: muscles move bones H: the muscles main job is to move bones 26

  27. Recognizing Faceted Entailment T: muscles move bones H: the muscles main job is to move bones 27

  28. Recognizing Faceted Entailment T: muscles move bones H: the muscles main job is to move bones 28

  29. What did we do? 29

  30. Approach: Leverage Existing Methods 30

  31. Approach: Leverage Existing Methods 31

  32. Approach: Leverage Existing Methods Exact Match penicillin cures pneumonia (penicillin, cure) Lexical Inference (penicillin, cure) pneumonia is treated by penicillin Lexical-Syntactic Inference P: 96%, R: 30% 32

  33. Approach: Leverage Existing Methods Exact Match penicillin cures pneumonia (penicillin, cure) Lexical Inference (penicillin, cure) pneumonia is treated by penicillin Lexical-Syntactic Inference P: 96%, R: 30% 33

  34. Approach: Leverage Existing Methods Exact Match penicillin cures pneumonia (penicillin, cure) Lexical Inference pneumonia is treated by penicillin (penicillin, cure) Lexical-Syntactic Inference WordNet 34

  35. Approach: Leverage Existing Methods Exact Match penicillin cures pneumonia (penicillin, cure) Lexical Inference pneumonia is treated by penicillin (penicillin, cure) Lexical-Syntactic Inference WordNet 35

  36. Approach: Leverage Existing Methods Exact Match penicillin cures pneumonia (penicillin, cure) Lexical Inference pneumonia is treated by penicillin (penicillin, cure) Lexical-Syntactic Inference penicillin cures pneumonia pneumonia is treated by penicillin 36

  37. Bar-Ilan University Textual Entailment Engine (Stern and Dagan, 2011) 37

  38. BIUTEE 38

  39. BIUTEE T H cures penicillin pneumonia 39

  40. BIUTEE T H cures treated penicillin pneumonia pneumonia is by penicillin 40

  41. BIUTEE T H cures treated penicillin pneumonia pneumonia is by penicillin 41

  42. cures penicillin pneumonia 42

  43. cures penicillin pneumonia cure treat (lexical) treats penicillin pneumonia 43

  44. cures penicillin pneumonia cure treat (lexical) treats penicillin pneumonia active passive (syntactic) treated pneumonia is by penicillin 44

  45. Facets to Dependencies treated pneumonia is by penicillin 45

  46. Facets to Dependencies treated pneumonia is by penicillin 46

  47. Decision Mechanisms Baseline Exact Match Exact Match OR Lexical Inference BaseLex BaseSyn Exact Match OR Syntactic Inference Lexical Inference Exact Match OR AND Syntactic Inference Majority 47

  48. Decision Mechanisms Baseline Exact Match Exact Match OR Lexical Inference BaseLex BaseSyn Exact Match OR Syntactic Inference Lexical Inference Exact Match OR AND Syntactic Inference Majority 48

  49. Decision Mechanisms Baseline Exact Match Exact Match OR WordNet BaseLex BaseSyn Exact Match OR BIUTEE Lexical Inference Exact Match OR AND Syntactic Inference Majority 49

  50. Decision Mechanisms Baseline Exact Match Exact Match OR WordNet BaseLex BaseSyn Exact Match OR BIUTEE WordNet Exact Match OR AND BIUTEE Majority 50

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