| tech,0-1-C90-3063,ak | capture <term> defeasibility </term> . <term> | Manual acquisition | </term> of <term> semantic constraints </term> | #20664 This paper proposes that sentence analysis should be treated as defeasible reasoning, and presents such a treatment for Japanese sentence analyses using an argumentation system by Konolige, which is a formalization of defeasible reasoning, that includes arguments and defeat rules that capture defeasibility.Manual acquisition of semantic constraints in broad domains is very expensive. | |
| lr,14-2-C90-3063,ak | <term> co-occurrence patterns </term> in a <term> | large corpus | </term> . To a large extent , these statistics | #20690 This paper presents an automatic scheme for collecting statistics on co-occurrence patterns in alarge corpus. | |
| other,19-3-C90-3063,ak | <term> anaphora references </term> and <term> | syntactic ambiguities | </term> . The scheme was implemented by gathering | #20712 To a large extent, these statistics reflect semantic constraints and thus are used to disambiguate anaphora references andsyntactic ambiguities. | |
| other,16-3-C90-3063,ak | </term> and thus are used to disambiguate <term> | anaphora references | </term> and <term> syntactic ambiguities </term> | #20709 To a large extent, these statistics reflect semantic constraints and thus are used to disambiguateanaphora references and syntactic ambiguities. | |
| other,6-1-C90-3063,ak | <term> semantic constraints </term> in <term> | broad domains | </term> is very expensive . This paper presents | #20670 Manual acquisition of semantic constraints inbroad domains is very expensive. | |
| model,3-1-C90-3063,ak | . <term> Manual acquisition </term> of <term> | semantic constraints | </term> in <term> broad domains </term> is very | #20667 Manual acquisition ofsemantic constraints in broad domains is very expensive. | |
| model,10-2-C90-3063,ak | scheme for collecting statistics on <term> | co-occurrence patterns | </term> in a <term> large corpus </term> . To | #20686 This paper presents an automatic scheme for collecting statistics onco-occurrence patterns in a large corpus. | |
| other,12-4-C90-3063,ak | on the <term> output </term> of other <term> | linguistic tools | </term> . An experiment was performed to | #20727 The scheme was implemented by gathering statistics on the output of otherlinguistic tools. | |
| model,8-3-C90-3063,ak | extent , these statistics reflect <term> | semantic constraints | </term> and thus are used to disambiguate | #20701 To a large extent, these statistics reflectsemantic constraints and thus are used to disambiguate anaphora references and syntactic ambiguities. | |
| other,6-5-C90-3063,ak | experiment was performed to resolve <term> | references | </term> of the <term> pronoun </term> it in sentences | #20736 An experiment was performed to resolvereferences of the pronoun it in sentences that were randomly selected from the corpus. | |
| model,13-6-C90-3063,ak | show that in most of the cases the <term> | cooccurrence statistics | </term> indeed reflect the <term> semantic | #20764 The results of the experiment show that in most of the cases thecooccurrence statistics indeed reflect the semantic constraints and thus provide a basis for a useful disambiguation tool. | |
| lr,19-5-C90-3063,ak | that were randomly selected from the <term> | corpus | </term> . The results of the experiment show | #20749 An experiment was performed to resolve references of the pronoun it in sentences that were randomly selected from thecorpus. | |
| other,9-5-C90-3063,ak | resolve <term> references </term> of the <term> | pronoun | </term> it in sentences that were randomly | #20739 An experiment was performed to resolve references of thepronoun it in sentences that were randomly selected from the corpus. | |
| other,9-4-C90-3063,ak | implemented by gathering statistics on the <term> | output | </term> of other <term> linguistic tools </term> | #20724 The scheme was implemented by gathering statistics on theoutput of other linguistic tools. | |
| model,18-6-C90-3063,ak | statistics </term> indeed reflect the <term> | semantic constraints | </term> and thus provide a basis for a useful | #20769 The results of the experiment show that in most of the cases the cooccurrence statistics indeed reflect thesemantic constraints and thus provide a basis for a useful disambiguation tool. | |
| other,28-6-C90-3063,ak | thus provide a basis for a useful <term> | disambiguation tool | </term> . <term> Spelling-checkers </term> have | #20779 The results of the experiment show that in most of the cases the cooccurrence statistics indeed reflect the semantic constraints and thus provide a basis for a usefuldisambiguation tool. |
