Incremental Parsing with Adjoining Operation

Kato, Yoshihide; Matsubara, Shigeki

doi:10.1587/transinf.e92.d.2306

Cited by 5 publications

(10 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The partial parse trees connect all words in each initial fragment of the sentence. Collins and Roark [11] and Kato and Matsubara [12] have proposed incremental parsing methods in which the parsing process proceeds on a word-by-word basis by using allowable chains. An allowable chain is a sequence of nonterminal symbols followed by a terminal symbol.…”

Section: Incremental Parsermentioning

confidence: 99%

Identifying Nonlocal Dependencies in Incremental Parsing

Kato

Matsubara

2015

IEICE Trans. Inf. & Syst.

Self Cite

View full text Add to dashboard Cite

SUMMARYThis paper describes a method of identifying nonlocal dependencies in incremental parsing. Our incremental parser inserts empty elements at arbitrary positions to generate partial parse trees including empty elements. To identify the correspondence between empty elements and their fillers, our method adapts a hybrid approach: slash feature annotation and heuristic rules. This decreases local ambiguity in incremental parsing and improves the accuracy of our parser.

show abstract

Section: Incremental Parsermentioning

confidence: 99%

Identifying Nonlocal Dependencies in Incremental Parsing

Kato

Matsubara

2015

IEICE Trans. Inf. & Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…We call this parse tree. Our method constructs a parse tree according to an incremental parsing formalism proposed in (Kato and Matsubara, 2009). This formalism extends the incremental parsing of (Collins and Roark, 2004) by introducing adjoining operation used in Tree Adjoining Grammar (Joshi, 1985).…”

Section: Incremental Construction Of Ccg Derivationmentioning

confidence: 99%

“…The incremental parsing assigns partial parse trees for any initial fragments of a sentence. Adjoining operation reduces local ambiguity caused by left-recursive structure, and improves the parsing accuracy (Kato and Matsubara, 2009). Furthermore, in the field of psycholinguistics, adjoining operation is introduced to a human sentence processing model (e.g., (Sturt and Lombardo, 2005;Mazzei et al, 2007;Demberg et al, 2013)).…”

Section: Incremental Construction Of Ccg Derivationmentioning

confidence: 99%

“…This section gives a formal description of incremental parsing of (Kato and Matsubara, 2009). The 271 parsing grammar consists of three types of elements: allowable tuples, allowable chains and auxiliary trees.…”

Section: A Formal Description Of Incremental Parsingmentioning

confidence: 99%

“…5 On the other hand, our method can use CCG-based lexicon (e.g., (Bos, 2009)) directly. Although our method requires a set of allowable chains and auxiliary trees in addition to such a lexicon, we can easily extract it from CCGbank (Hockenmaier and Steedman, 2007) by using the method proposed in (Kato and Matsubara, 2009). …”

Section: Semantic Construction Using Adjoiningmentioning

confidence: 99%

See 2 more Smart Citations

Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics

2015

View full text Add to dashboard Cite

will take place in Denver on June 4 and 5 and is colocated with SemEval and NAACL. As in 2014 at COLING, also on this occasion *SEM and SemEval chose to coordinate their programs by featuring a joint invited talk. In this way, *SEM aims to bring together the ACL SIGLEX and ACL SIGSEM communities.The acceptance rate of *SEM 2015 was quite competitive: out of 98 submissions, we accepted 36 papers for an overall acceptance of 37%. The acceptance rate of long paper that were accepted for oral presentation (18 out of 62) is 29%. The papers cover a wide range of topics including distributional semantics; lexical semantics and lexical acquisition; formal and linguistic semantics; discourse semantics; lexical resources, linked data and ontologies; semantics for applications; and extra-propositional semantics: sentiment and figurative meaning.The *SEM 2015 program consists of oral presentations for selected long papers and a poster session for long and short papers.Day One, June 4th:• Joint *SEM SemEval keynote talk by Marco Baroni;• Oral presentation sessions on distributional semantics, lexical semantics, and extra-propositional semantics;• Poster session.Day Two, June 5th:• Keynote talk by Preslav Natkov;• Oral presentation sessions on semantics for applications, lexical resources and ontologies, formal semantics, and discourse semantics;• *SEM Best Paper Award.We cannot finish without saying that *SEM 2015 would not have been possible without the considerable efforts of our area chairs, their reviewers, and the computational semantics community in general.We hope you will enjoy *SEM 2015, Distributional semantic methods have some a priori appeal as models of human meaning acquisition, because they induce word representations from contextual distributions naturally occurring in corpus data without need for supervision. However, learning the meaning of a (concrete) word also involves establishing a link between the word and its typical visual referents, which is beyond the scope of classic, text-based distributional semantics. Since recently several proposals have been put forward about how to induce multimodal word representations from linguistic and visual contexts, it is natural to ask if this line of work, besides its practical implications, can help us to develop more realistic, grounded models of human word learning within the distributional semantics framework.In my talk, I will report about two studies in which we used multimodal distributional semantics (MDS) to simulate human word learning. In one study, we first measured the ability of subjects to link a nonce word to relevant linguistic and visual associates when prompted only by exposure to minimal corpus evidence about it. We then simulated the same task with an MDS model, finding its behavior remarkably similar to that of subjects. In the second study, we constructed a corpus in which child-directed speech is aligned with real-life pictures of the objects mentioned by care-givers. We then trained our MDS model on these data, and inspected the generaliza...

show abstract

Incremental Semantic Construction Based on Combinatory Categorial Grammar

Kato

Matsubara

2016

IEICE Trans. Inf. & Syst.

Self Cite

View full text Add to dashboard Cite

SUMMARYThis paper proposes a method of incrementally constructing semantic representations. Our method is based on Steedman's Combinatory Categorial Grammar (CCG), which has a transparent correspondence between syntax and semantics. In our method, a derivation for a sentence is constructed in an incremental fashion and the corresponding semantic representation is derived synchronously. Our method uses normal form CCG derivation. This is the difference between our approach and previous ones. Previous approaches use most left-branching derivation called incremental derivation, but they cannot process coordinate structures incrementally. Our method overcomes this problem.

show abstract

Incremental Parsing with Adjoining Operation

Cited by 5 publications

References 15 publications

Identifying Nonlocal Dependencies in Incremental Parsing

Identifying Nonlocal Dependencies in Incremental Parsing

Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics

Incremental Semantic Construction Based on Combinatory Categorial Grammar

Contact Info

Product

Resources

About