Abstract: Separate structural units for an inner gear and a housing of a planetary gear device include an inner gear with a first raised portion formed on the outer peripheral surface of the inner gear, where the first raised portion extends towards in a direction that is inclined with respect to the axial direction of the inner gear. A housing includes a second raised portion formed on an inner peripheral surface, where the second raised portion extends in a direction that is inclined in respect to the axial direction. The housing contains the inner gear such that there is a gap formed between the inner peripheral surface of the housing and the outer peripheral surface of the inner gear. Movement of the inner gear within the interior of the housing is limited through linear contact of the first raised portion and the second raised portion.

Abstract: In an inference device, an observation input means receives an observation as an input. A hypothesis candidate generation means generates hypothesis candidates by applying inference knowledge to the observation in the backward direction. The problem conversion means converts the hypothesis candidate into an ILP problem or a SAT problem. An equivalent problem generation means generates a specified number of equivalent ILP problems or equivalent SAT problems in which an order of the variables included in the converted ILP problem or SAT problem is changed. The solver parallelization means solves the generated equivalent ILP problems or equivalent SAT problems by executing a specified number of identical ILP solvers or SAT solvers in parallel. The optimal solution output means outputs a result of the ILP solver or the SAT solver that output the result first, among the specified number of ILP solvers or SAT solvers, as the optimal solution.

Abstract: Separate structural units for an inner gear and a housing of a planetary gear device include an inner gear with a first raised portion formed on the outer peripheral surface of the inner gear, where the first raised portion extends towards in a direction that is inclined with respect to the axial direction of the inner gear. A housing includes a second raised portion formed on an inner peripheral surface, where the second raised portion extends in a direction that is inclined in respect to the axial direction. The housing contains the inner gear such that there is a gap formed between the inner peripheral surface of the housing and the outer peripheral surface of the inner gear. Movement of the inner gear within the interior of the housing is limited through linear contact of the first raised portion and the second raised portion.

Abstract: An inferential knowledge construction support apparatus 1 has a literal generation unit 2 that generates literal information based on the extracted elements, a rule generation unit 3 that estimates a causal or implicational relation between literals, using plural pieces of literal information, and generates rule information by allocating literal information estimated to be in the causal/implicational relation to an antecedent and a consequent, a display information generation unit 4 that generates display information to be used for causing a display device to output a rule editing user interface for displaying, in a juxtaposed manner, a literal display area for displaying the literal information and descriptive information corresponding to the literal information and a rule display area for displaying the rule information and descriptive information corresponding to the rule information, and an editing unit 5 that enables an operator to edit the rule information, using the rule editing user interface.

Abstract: A hypothesis verification apparatus 100, includes a hypothesis generation unit 11 that derives hypothesis candidates having a logical formula leading to possible consequences from an observation data, a hypothesis integration unit 12 that integrate the logical formula of each of the hypothesis candidates to construct a logical formula set, and, when there are overlapping logical formula select only one of them, a hypothesis verification unit 13 that sets, when a logical formula including a first parameter and a second parameter is existing in the logical formula set, the logical formula as a target logical formula, and input the acquired value of the second parameter into the target logical formula, and on the other hand, when logical formula is not existing, but if a logical formula that has a value in advance or has a value obtained by inference knowledge is existing, determine truth or falsehood of the existing logical formula.

Abstract: An information processing apparatus (10) includes a speech act formula generation unit (12) and an adjacency pair extraction unit (14). Dialogue text described in natural language is input to the speech act formula generation unit (12). The adjacency pair extraction unit (14) extracts, using preset pair information, pairs of speech act formulas that indicate adjacency pairs, from a plurality of speech act formulas generated by the speech act formula generation unit (12). Specifically, the adjacency pair extraction unit (14) extracts, as a pair of speech act formulas indicating an adjacency pair, a speech act formula generated from an arbitrary utterance text passage in the dialog text and one of a plurality of speech act formulas generated from a plurality of other utterance text passages, the one speech act formula including a predicate that forms a predicate pair with a predicate included in the arbitrary speech act formula.

Abstract: An entailment pattern pair extension apparatus 50 extends entailment pairs by generating an n-term entailment pair from an m-term entailment pair, where m and n are integers not smaller than 0 and satisfying m<n. Each entailment pair includes a first language pattern and a second language pattern entailed by the first language pattern. Entailment pattern pair extension apparatus 50 includes: a generation rule storage unit 110 storing generation rules for generating n-term entailment pairs from m-term entailment pairs, and a binary pair adding unit 112 receiving m-term entailment pair, determining, for each generation rule stored in the generation rule storage unit 110, whether its condition is satisfied by the m-term pair, and if the condition is satisfied, applying a modification rule of the generation rule to each language pattern constituting the m-term entailment pair.

Abstract: [Object] To provide a device assisting a user to easily generate, in relation to an issue of interest to the user, a question sentence guaranteed to have an answer of a certain accuracy or higher in a question-answering system. [Solution] A question sentence generating device is used with a question-answering system, and it includes: word receiving means for receiving a word 480 as a source for generating a question sentence; and question sentence generating database 502 comprised of a plurality of entries for generating a question sentence. Each of the plurality of entries has a word as a key and includes an answer sentence pattern co-occurring with the word, used in the question-answering system.

Abstract: An entailment pattern pair extension apparatus 50 extends entailment pairs by generating an n-term entailment pair from an m-term entailment pair, where m and n are integers not smaller than 0 and satisfying m<n. Each entailment pair includes a first language pattern and a second language pattern entailed by the first language pattern. Entailment pattern pair extension apparatus 50 includes: a generation rule storage unit 110 storing generation rules for generating n-term entailment pairs from m-term entailment pairs, and a binary pair adding unit 112 receiving m-term entailment pair, determining, for each generation rule stored in the generation rule storage unit 110, whether its condition is satisfied by the m-term pair, and if the condition is satisfied, applying a modification rule of the generation rule to each language pattern constituting the m-term entailment pair.

Abstract: [Object] To provide a device assisting a user to easily generate, in relation to an issue of interest to the user, a question sentence guaranteed to have an answer of a certain accuracy or higher in a question-answering system. [Solution] A question sentence generating device is used with a question-answering system, and it includes: word receiving means for receiving a word 480 as a source for generating a question sentence; and question sentence generating database 502 comprised of a plurality of entries for generating a question sentence. Each of the plurality of entries has a word as a key and includes an answer sentence pattern co-occurring with the word, used in the question-answering system.

Abstract: In order to provide a non-factoid question answering system with improved precision, the question answering system (160) includes: a candidate retrieving unit (222), responsive to a question, extracting answer candidates from a corpus storage (178); a feature vector generating unit (232) for generating features from combinations of a question with each of the answer candidates; SVMs (176) trained to calculate a score of how correct a combination of the question with an answer candidate is, upon receiving the feature vector therefor; and an answer ranker unit (234) outputting the answer candidate with the highest calculated score as the answer. The features are generated on the basis of the results of morphological analysis and parsing of the question, a phrase in the question evaluated as being positive or negative as well as its polarity, and the semantic classes of nouns in the features.

Abstract: In order to provide a non-factoid question answering system with improved precision, the question answering system (160) includes: a candidate retrieving unit (222), responsive to a question, extracting answer candidates from a corpus storage (178); a feature vector generating unit (232) for generating features from combinations of a question with each of the answer candidates; SVMs (176) trained to calculate a score of how correct a combination of the question with an answer candidate is, upon receiving the feature vector therefor; and an answer ranker unit (234) outputting the answer candidate with the highest calculated score as the answer. The features are generated on the basis of the results of morphological analysis and parsing of the question, a phrase in the question evaluated as being positive or negative as well as its polarity, and the semantic classes of nouns in the features.