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TGM v1Template generation Description Templator is a module for dependency-driven SPARQL template generation from natural language. Templator takes in a question and generates pseudo-queries as well as a list of strings (so-called slots) for which data from the knowledge base is needed. Approach First, the question is linguistically analysed, annotating it with part-of-speech tags, dependency relations, and semantic role labels. Second, the resulting parse tree is transformed into a template, covering one possibility of the how natural language expressions correspond to constructs in the target SPARQL query. This is the template that is most faithful to the linguistic structure of the question. In order to also account for structural differences between the question and the target query, the template is modified by a sequence of steps that collapse or expand triples, yielding additional templates. The scoring of the templates follows a simple heuristics computing the number of nodes in the query body that are neither projection variables nor slots. In addition, each rewriting operation reduces the score by a predetermined factor. Function 1. NLP tools (e.g. the stanford parser) analyze the input question text into dependency parse tree. 2. Then Templator generates the pseudo query for SPARQL query based on the RULEs within dependency parse tree Scope and limit Current version (March, 2016) focused on the hand-crafted RULEs for dependency parse tree. So that the QA performance depends on the RULEs' quality and coverage. Issues and discusion * How to check/add/edit RULEs? ~/src/main/resources/rules/ - RULEs for English: SRL_rules_en.json - RULEs for Korean: SRL_rules_ko.json At this time (January 13, 2016, at OKBQA 3.5) we can not provide yet the web service to add/edit exist RULEs or use your own RULEs for the OKBQA platform. This web service would be provided before/during OKBQA 4 (http://4.okbqa.org) We believe that good RULEs would improve overall performance of (our/your own) QA system. * Does it works for Korean? It currently works for English and Korean. Yes. We've added simple RULEs for some Korean question words such as "무엇", "누구", "어떤", and "얼마나 많". Of course, this rules cover few cases. Now you can test this sentence: "어떤 강이 서울을 흐르는가?" using the following Sample curl command. * How to deploy it: $ git clone https://github.com/okbqa/templator $ cd templator $ mvn compile exec:java Source code Implementations are available on GitHub: github.com/okbqa/templategeneration github.com/okbqa/templator Contacts While general questions about Templator should be addressed to the original developer, Christina Unger {cunger@cit-ec.uni-bielefeld.de}, Younggyun Hahm {hahmyg@kaist.ac.kr} also can act as a contact point especially for the matter on Korean applications. 2015-08-28 01:21:29 UTCcunger@cit-ec.uni-bielefeld.de
TGM v2Template generation Description Module for dependency-driven SPARQL template generation from natural language, for English and Korean. It takes in a question and generates pseudo-queries as well as a list of strings (so-called slots) for which data from the knowledge base is needed. Approach First, the question is linguistically analysed, annotating it with part-of-speech tags, dependency relations, and semantic role labels. Second, the resulting parse tree is transformed into a template, covering one possibility of the how natural language expressions correspond to constructs in the target SPARQL query. This is the template that is most faithful to the linguistic structure of the question. The scoring of the templates follows a simple heuristics computing the number of nodes in the query body that are neither projection variables nor slots. A documentation of the rule format can be found in the GitHub repository: https://github.com/okbqa/rocknrole/tree/master/src/main/resources/rules Scope and limit It relies on hand-crafted rules for transforming dependency parses into templates, so its quality and coverage is only as good as the rules. How to deploy it $ git clone https://github.com/okbqa/rocknrole $ cd rocknrole $ ./deploy.sh Contact For general questions and problems, get in touch with Christina Unger {cunger@cit-ec.uni-bielefeld.de}. For questions related to Korean, you can also get in touch with Younggyun Hahm {hahmyg@kaist.ac.kr}.2016-07-19 07:37:34 UTCcunger@cit-ec.uni-bielefeld.de
EvaluatorEvaluation Description Evaluator is a module to evaluate given question answering system, based on the user's choice of modules. Users can make use of configuration options to choose which modules to use for the steps of QA system. Once evalutor runs, it sends a natural language question in answer dataset to Controller one-by-one. It compares true answer of the dataset with the answer list from Controller to calculate accuracy of the system. Function Evaluator evaluates the overall QA system using answer set. For instance, let the answer set contains only two sentences, "Which rivers flow through Seoul?" and "Who is the author of 'Samguk Sagi'?" In addition, suppose that Controller success to give correct answer for the former question, but fails for the latter one. Then, Evaluator would return accuracy 1/2 = 0.5 to the user. Scope and limit The only dataset usable for the Evalator is NLQ-1 dataset, which contains question-answer pair for only Korean and English at the moment (March, 2016) with 40 questions in the set. Since Evaluator works for measuring accuracy of the given QA system, it is not suitable for analyzing each test case. For the purpose, you may use website for Controller or website for Evaluator (which supports dump file for each question). Issues and discussion * Is it possible to make use of another answer set like QALD-4? Not yet (January 13, 2016, OKBQA3.5). However, supporting mult-answer sets would be added at OKBQA4(http://4.okbqa.org) * Can I test my own QA system? Since Evaluator calls Controller to retrieve answers of each questions, only QA system following OKBQA system structure (TGM, DM, AGM) is applicable. This structure is targetted for those who want to add their own modules to the OKBQA system structure, and checks the performance of it. Maintainer: Sang-min An {asm427@kaist.ac.kr}2016-01-13 16:26:23 UTCasm427@kaist.ac.kr
StarGraph Disambiguation Module Disambiguation Disambiguation module which uses distributional semantics for mapping terms to entities.2016-07-21 02:17:27 UTCandrenfreitas@gmail.com
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