ISO/TC37/SC4 TDG3 Discourse Relations

1. ISO/TC37/SC4 TDG3Discourse Relations HASIDA Koiti hasida.k@aist.go.jp ITRI, AIST, Japan

2. Issues • Definition • Applications • Granularity • Headedness • Taxonomy • Wrapped Arguments • Relation with Other Tasks

3. Definition A discourse relation is • a relation among events, states of affairs, and/or their types • [I worked hard] to [pass the exam]. • semantic (informational), pragmatic (presentational), or both. • [Tom came] because [Mary came]. • = [I infer [Tom came]] because [Mary came]. event (arg1) purpose relation event type (arg2) conclusion pragmatic evidence result semantic cause

4. Applications • Description of pragmatic/semantic structure of discourse • Semantic Authoring • improvement of quality • reduction of cost

5. Granularity • Relations vs. Discourse Connectives • Rhetorical Structure Theory (RST) • 40～80 relations • Penn Discourse TreeBank (PDTB) • 250 explicit connectives • Ichikawa (1957, 1963, 1978) • about 30 relations • Infinitely many non-synonymous connectives • e.g., fifteen minutes after

6. Headedness • Which argument of a discourse relation is the head (nucleus) may depend on the context. • Discourse graph (next page) • Semantic authoring may use relations underspecified in terms of headedness.

7. Discourse Graph (not Tree) • A huge amount of content is necessary to implement ubiquitous information service. • So content must be easy to create. • Also, the retrieval of content must be quick and easy to implement ubiquitous information service. • Hence semantic annotation is necessary. • So intelligent content technology is necessary.

8. Taxonomy • RST: relations • mononuclear (single head) • presentational, subject-matter (informational) • multinuclear (multiple heads) • PDTB: connectives • explicit • conjunction • subordinate, coordinate • adverbial • implicit

9. Taxonomy (cont.) • Ichikawa • binary logical relations • derivation, concessive, others • multilateral relations • addition, comparison, diversion, others • elaborative relations • parallelism, complement, chain • Merging RST and Ichikawa • about 50 relations, modulo headedness

10. Wrapped Arguments • A discourse relation may concern not the whole argument but its core wrapped in an attitude report, a modal operator, etc. • How to identify the core (real argument)? • explicit annotation Remember all those vegetables you slipped under the table ? arg2 you slipped under the table cause Maybe that’s why Sparky lived so long. arg1 Sparky lived so long

11. Explicit Annotation • Relations and their arguments should be annotated to specify the corresponding text spans. Remember all those vegetables you slipped under the table ? you slipped under the table equal arg1 result Maybe that ’s why Sparky lived so long. that arg2 Sparky lived so long

12. Relation with Other Tasks • Semantic Relations, Semantic Roles, Temporal Relations, and Quantifications • Overlap or Projection • [Tom came] at [8 o’clock]. • [Tom came] when [Mary came]. time (semantic role) equality or Projection? equality or projection? circumstance (discourse rel.)

13. Proposals • Granularity • multiple granularities in a hierarchical taxonomy • Headedness • discourse relations modulo headedness • Taxonomy • Ichikawa’s taxonomy as baseline • Wrapped Arguments • explicit annotation • Relation with Other Tasks • common relations to reduce their number

14. Appendix: General Guidelines

15. Name of Binary Relation • Naming Convention for Relation R • noun & adjective … arg2 is R of arg1. • subject, agent, patient, purpose, example, etc. • verb … arg1 R arg2. • includes, contains, etc. • preposition … arg1 isR arg2. • after, in, until, etc.