A Translation from Logic to English with Dynamic Semantics

author: Elizabeth Coppock, Cycorp Inc.
published: March 26, 2010, recorded: March 2010, views: 786

Slides

Slides
0:00	A Translation from logic to English with Dynamic Semantics
0:52	Outline - 1
1:01	General Program
1:49	Referring and non-referring expressions
2:19	Two separate fields in NLG
2:40	Generating Referring Expressions - 1
2:48	Generating Referring Expressions - 2
3:07	Generating Referring Expressions - 3
3:25	Generating Referring Expressions - 4
3:32	Generating "quantified" referring expressions
4:04	Tactical generation
4:28	Quantificational input
7:23	How to combine strenghts - 1
7:46	How to combine strenghts - 2
8:17	How to combine strenghts - 3
8:28	Dynamic Semantics - 1
8:56	Dynamic Semantics - 2
9:07	Dynamic Semantics - 3
9:30	Karttunen's discourse referents - 1
10:03	Karttunen's discourse referents - 2
10:22	DRT Example - 1
10:44	DRT Example - 2
11:48	DRT Example - 3
12:53	Discourse Representation Structures -1
13:07	Discourse Representation Structures -2
13:12	Discourse Representation Structures -3
13:15	A DRS is not a good point - 1
13:24	A DRS is not a good point - 2
13:39	A DRS is not a good point - 3
13:48	Present framework - 1
13:57	Present framework - 2
14:04	Present framework - 3
14:05	Outline - 2
14:18	Direct translation
15:14	A simple algorithm
15:30	The simple algorithm works in simple cases
15:43	Exception: Donkey sentences
16:51	Universally quantified variables under negation
17:26	No any in subject position
17:53	Relative scope matters
18:30	Existentials - indefinite
18:39	Existentially bound variables and negation
19:22	Existentially bound variables and negation, cont'd
21:49	Everyone needs anaphora
23:08	Short term referents - 1
23:24	Short term referents - 2
23:29	Short term referents - 3
23:44	Short term referents - 4
25:52	A better example - 1
25:59	A better example - 2
26:01	A better example - 3
26:08	A better example - 4
26:58	Different determiners, different lifespans
27:35	Our solution: Side effects - 1
27:55	Our solution: Side effects - 2
28:16	Our solution: Side effects - 3
28:23	Outline - 3
28:27	Discourse context
29:13	Letting discourse referents be constants - 1
29:46	Letting discourse referents be constants - 2
30:21	Letting discourse referents be constants - 3
30:59	What makes the semantics dynamic
31:30	Example - 1
31:56	Example - 2
32:00	Example - 3
32:03	Example - 4
32:08	Example - 5
32:18	Example - 6
32:32	Generation templates
33:24	Discourse referents corresponding to variables - 1
34:06	Discourse referents corresponding to variables - 2
34:08	Discourse referents corresponding to variables - 3
34:16	Discourse referents corresponding to variables - 4
34:19	Discourse referents corresponding to variables - 5
34:26	Discourse referents corresponding to variables - 6
35:46	Lifespan limitations - 1
36:17	Lifespan limitations - 2
36:24	Lifespan limitations - 3
36:27	Lifespan limitations - 4
36:29	Lifespan limitations - 5
36:31	Lifespan limitations - 6
36:39	Lifespan limitations - 7
36:46	Lifespan limitations - 8
36:51	Lifespan limitations - 9
36:54	Lifespan limitations - 10
36:56	Lifespan limitations - 11
36:57	Lifespan limitations - 12
37:03	Lifespan limitations - 13
37:10	Suppose we did not remove x from D - 1
37:10	Suppose we did not remove x from D - 2
37:11	Suppose we did not remove x from D - 3
37:12	Suppose we did not remove x from D - 4
37:14	Suppose we did not remove x from D - 5
37:17	Suppose we did not remove x from D - 6
37:18	Suppose we did not remove x from D - 7
37:19	Suppose we did not remove x from D - 8
37:20	Suppose we did not remove x from D - 9
37:21	Suppose we did not remove x from D - 10
37:21	Suppose we did not remove x from D - 11
37:38	Returning to Heim's cat example - 1
37:48	Returning to Heim's cat example - 2
37:52	Returning to Heim's cat example - 3
37:56	Returning to Heim's cat example - 4
37:58	Outline - 4
38:03	Operator Context: Definition - 1
38:34	Operator Context: Definition - 2
39:20	Clausal skeletons
40:21	Variable typing clauses - 1
40:33	Variable typing clauses - 2
40:40	Variable typing clauses - 3
40:48	Variable typing clauses - 4
40:57	Constructing clausal skeletons - 1
43:23	Constructing clausal skeletons - 2
44:00	Procedure - 1
44:08	Procedure - 2
44:17	Procedure - 3
47:24	Example: Donkey sentence - 1
47:40	Example: Donkey sentence - 2
47:49	Example: Donkey sentence - 3
47:53	Example: Eliminating the antecedent - 1
48:13	Example: Eliminating the antecedent - 2
48:21	Example: Eliminating the antecedent - 3
48:34	Negation stripping - 1
49:06	Negation stripping - 2
49:29	Negation stripping - 3
49:29	Negation stripping - 4
49:35	Updating the operator stack
51:32	Variable realization algorithm
52:12	Determiner selection algorithm - 1
53:10	Determiner selection algorithm - 2
53:20	Determiner selection algorithm - 3
54:45	Example: nothing - 1
54:50	Example: nothing - 2
55:03	Example: nothing - 3
55:14	Example: nothing - 4
55:17	Example: nothing - 5
55:21	Example: nothing - 6
55:24	Example: nothing - 7
55:29	Example: nothing - 8
56:03	Example: nothing - 9
56:16	Example: anything - 1
56:27	Example: anything - 2
56:31	Example: anything - 3
56:39	Example: anything - 4
56:40	Example: anything - 5
56:41	Example: anything - 6
56:43	Example: anything - 7
56:48	Example: anything - 8
56:54	Example: anything - 9
57:04	Example: anything - 10
58:12	Example: not ... everything - 1
58:21	Example: not ... everything - 2
58:26	Example: not ... everything - 3
58:37	Example: not ... everything - 4
58:38	Example: not ... everything - 5
58:39	Example: not ... everything - 6
58:39	Example: not ... everything - 7
58:43	Example: not ... everything - 8
58:45	Example: not ... everything - 9
59:00	Example: not ... everything - 10
59:00	Example: Donkey sentence - 4
59:07	Example: Donkey sentence - 5
59:14	Example: Donkey sentence - 6
59:14	Example: Donkey sentence - 7
59:16	Example: Donkey sentence - 8
59:33	Example: Donkey sentence - 9
59:34	Example: Donkey sentence - 10
59:35	Example: Donkey sentence - 11
59:36	Example: Donkey sentence - 12
59:38	Example: Donkey sentence - 13
59:40	Example: Donkey sentence - 14
59:47	Example: Donkey sentence - 15
59:49	Interaction between determiners and lifespans - 1
60:06	Interaction between determiners and lifespans - 2
60:24	Interaction between determiners and lifespans - 3
60:27	Interaction between determiners and lifespans - 4
60:37	Interaction between determiners and lifespans - 5
60:38	Interaction between determiners and lifespans - 6
60:40	Interaction between determiners and lifespans - 7
60:41	Interaction between determiners and lifespans - 8
60:42	Interaction between determiners and lifespans - 9
60:46	Interaction between determiners and lifespans - 10
61:10	Interaction between determiners and lifespans - 11
61:14	Interaction between determiners and lifespans - 12
61:17	Outline - 5
61:20	Summary - 1
61:34	Summary - 2
61:51	Summary - 3
62:04	Outlook
65:03	Thank you

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Description

We present a procedure for translating standard predicate logic into English. The procedure generates both referring expressions and non-referring expressions, including both referential and bound variable anaphora. Non-referring expressions correspond to short-term discourse referents [1], which present a special set of challenges for a natural language generation system: (i) they have limited ‘lifespans’ and (ii) the determiner with which they are introduced (every, some, any, no) is sensitive to the logical context. Our system addresses these challenges using dynamically updated information states.