• Title, Summary, Keyword: semantic parsing

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Assisting semantic parsing-based QA system with lexico-semantic pattern query template (Semantic parsing 기반 지식 베이스 질의응답 시스템의 어휘-의미 패턴 질의 템플릿을 통한 보완)

  • Shim, Hyosup;Park, Seonyeong;Lee, Gary Geunbae
    • Annual Conference on Human and Language Technology
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    • pp.255-258
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    • 2014
  • 본 논문에서는 semantic parsing과 사전 정의된 어휘-의미 패턴 질의 템플릿 방법론을 결합하여 자연어 질의로부터 RDF 지식베이스에 질의하기 위한 SPARQL 쿼리를 생성하는 방법을 제안한다. semantic parsing 접근법은 문장의 표현과 분리된 형식적 의미표현만을 포착해내므로, paraphrase 혹은 의미 변화와 무관한 어순의 변화에 강인하지만, 일부 자연어 질의문장에는 단순한 의미 및 구조를 갖는 문장도 적합한 형식적 의미표현을 생성하지 못하는 단점이 있다. 따라서 이 연구에서는 이러한 단순한 문장에 있어서는 사전 정의된 질의 템플릿을 사용하여 적합한 쿼리를 생성하되, 적합한 템플릿을 선택하는데 있어 해당 질의문장의 어휘-의미적 유형을 포착하고 해당 정보를 이용하는 방법을 이용하였으며 이를 통해 주 방법론의 약점을 보완하는 제한적인 효과를 얻을 수 있었다.

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Two-Phase Shallow Semantic Parsing based on Partial Syntactic Parsing (부분 구문 분석 결과에 기반한 두 단계 부분 의미 분석 시스템)

  • Park, Kyung-Mi;Mun, Young-Song
    • The KIPS Transactions:PartB
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    • v.17B no.1
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    • pp.85-92
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    • 2010
  • A shallow semantic parsing system analyzes the relationship that a syntactic constituent of the sentence has with a predicate. It identifies semantic arguments representing agent, patient, instrument, etc. of the predicate. In this study, we propose a two-phase shallow semantic parsing model which consists of the identification phase and the classification phase. We first find the boundary of semantic arguments from partial syntactic parsing results, and then assign appropriate semantic roles to the identified semantic arguments. By taking the sequential two-phase approach, we can alleviate the unbalanced class distribution problem, and select the features appropriate for each task. Experiments show the relative contribution of each phase on the test data.

A Two-Phase Shallow Semantic Parsing System Using Clause Boundary Information and Tree Distance (절 경계와 트리 거리를 사용한 2단계 부분 의미 분석 시스템)

  • Park, Kyung-Mi;Hwang, Kyu-Baek
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.5
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    • pp.531-540
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    • 2010
  • In this paper, we present a two-phase shallow semantic parsing method based on a maximum entropy model. The first phase is to recognize semantic arguments, i.e., argument identification. The second phase is to assign appropriate semantic roles to the recognized arguments, i.e., argument classification. Here, the performance of the first phase is crucial for the success of the entire system, because the second phase is performed on the regions recognized at the identification stage. In order to improve performances of the argument identification, we incorporate syntactic knowledge into its pre-processing step. More precisely, boundaries of the immediate clause and the upper clauses of a predicate obtained from clause identification are utilized for reducing the search space. Further, the distance on parse trees from the parent node of a predicate to the parent node of a parse constituent is exploited. Experimental results show that incorporation of syntactic knowledge and the separation of argument identification from the entire procedure enhance performances of the shallow semantic parsing system.

Ontology Parser Design for Speed Improvement of Ontology Parsing (온톨로지 파싱 속도향상을 위한 온톨로지 파서 설계)

  • Kim, Won-Pil;Kong, Hyun-Jang
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.4
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    • pp.96-101
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    • 2010
  • The core study of semantic web is the efficiency of ontology parsing. The ontology parsing and inference is based on the significant information retrieval which is the ultimate purpose of semantic web. However, most existing ontology writing tools were not processing the efficient ontology parsing. Therefore, we design the two steps ontology parser for extracting the all facts, are included in the ontology, more fast in this study. In the first step, the token extractor collects the all tokens of ontology and the triple extractor extracts the statements in the collected tokens. In conclusion, we confirm that which is designed in this study, processes the ontology parsing more faster than the existing ontology parsers.

CFG based Korean Parsing Using Sentence Patterns as Syntactic Constraint (구문 제약으로 문형을 사용하는 CFG기반의 한국어 파싱)

  • Park, In-Cheol
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.9 no.4
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    • pp.958-963
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    • 2008
  • Korean language has different structural properties which are controlled by semantic constraints of verbs. Also, most of Korean sentences are complex sentences which consisted of main clause and embedded clause. Therefore it is difficult to describe appropriate syntactic grammar or constraint for the Korean language and the Korean parsing causes various syntactic ambiguities. In this paper, we suggest how to describe CFG-based grammar using sentence patterns as syntactic constraint and solve syntactic ambiguities. To solve this, we classified 44 sentence patterns including complex sentences which have subordinate clause in Korean sentences and used it to reduce syntactic ambiguity. However, it is difficult to solve every syntactic ambiguity using the information of sentence patterns. So, we used semantic markers with semantic constraint. Semantic markers can be used to solve ambiguity by auxiliary particle or comitative case particle.

Transition and Parsing State and Incrementality in Dynamic Syntax

  • Kobayashi, Masahiro;Yoshimoto, Kei
    • Proceedings of the Korean Society for Language and Information Conference
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    • pp.249-258
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    • 2007
  • This paper presents an implementation of a gramar of Dynamic Syntax for Japanese. Dynamic Syntax is a grammar formalism which enables a parser to process a sentence in an incremental fashion, establishing the semantic representation. Currently the application of lexical rules and transition rules in Dynamic Syntax is carried out arbitrarily and this leads to inefficient parsing. This paper provides an algorithm of rule application and partitioned parsing state for efficient parsing with special reference to processing Japanese, which is one of head-final languages. At the present stage the parser is still small but can parse scrambled sentences, relative clause constructions, and embedded clauses. The parser is written in Prolog and this paper shows that the parser can process null arguments in a complex sentence in Japanese.

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Parsing the Wh-Interrogative Construction in Korean

  • Yang, Jaehyung;Kim, Jong-Bok
    • Language and Information
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    • v.17 no.2
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    • pp.51-66
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    • 2013
  • Korean is a wh-in-situ language where the wh-expression stays in situ with an obligatory Q-particle marking its interrogative scope. This paper briefly reviews some basic properties of the wh-question construction in Korean and shows how a typed feature structure grammar, HPSG (Pollard and Sag 1994, Sag et al. 2003), together with the notions of 'type hierarchy' and 'constructions', can provide a robust basis for parsing the wh-construction in the language. We show that this system induces robust syntactic structures as well as enriched semantic representations for real-time applications such as machine translation, which require deep processing of the phenomena concerned.

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An Automatic News Video Semantic Parsing Algorithm (뉴스 동영상 자동 의미 분석 알고리즘)

  • 전승철;박성한
    • Proceedings of the IEEK Conference
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    • pp.109-112
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    • 2001
  • This paper proposes an efficient algorithm of extracting anchor blocks for a semantic structure of a news video. We define the FRFD to calculate the frame difference of anchor face position rather than simply uses the general frame difference. Since, The FRFD value is sensitive to existing face in frame, anchor block can be efficiently extracted. In this paper, an algorithm to extract a face position using partial decoded MPEG data is also proposed. In this way a news video can be structured semantically using the extracted anchor blocks.

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A Parallel Speech Recognition Model on Distributed Memory Multiprocessors (분산 메모리 다중프로세서 환경에서의 병렬 음성인식 모델)

  • 정상화;김형순;박민욱;황병한
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.5
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    • pp.44-51
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    • 1999
  • This paper presents a massively parallel computational model for the efficient integration of speech and natural language understanding. The phoneme model is based on continuous Hidden Markov Model with context dependent phonemes, and the language model is based on a knowledge base approach. To construct the knowledge base, we adopt a hierarchically-structured semantic network and a memory-based parsing technique that employs parallel marker-passing as an inference mechanism. Our parallel speech recognition algorithm is implemented in a multi-Transputer system using distributed-memory MIMD multiprocessors. Experimental results show that the parallel speech recognition system performs better in recognition accuracy than a word network-based speech recognition system. The recognition accuracy is further improved by applying code-phoneme statistics. Besides, speedup experiments demonstrate the possibility of constructing a realtime parallel speech recognition system.

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