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US 2018/0018573 A1Published application
Vector operators for distributional entailment
AssigneeXerox Corporation
InventorsJames Brinton Henderson, Diana Nicoleta Popa
Life of this patent
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Abstract
A system and method for making entailment inferences are disclosed. Entailment inferences are computed between semantic representations of text objects which, for a set of features, indicate whether the feature is known or unknown about the text object. A function of the semantic representations of first and second text objects is computed with an asymmetric vector space operator which differs depending on the entailment relationship.
Claims21
A method for making an entailment inference, comprising:
- with a processor, computing an entailment inference for a first text object with respect to a second text object, comprising computing a function of semantic representations of the first and second text objects with an asymmetric vector space operator;
- and
- outputting information based on the inference.
An entailment system comprising:
- a representation generation component which generates semantic representations of text objects using a trained semantic model, each semantic representation comprising a multidimensional vector;
- an inference component which computes an entailment inference for a first text object with respect to a second text object, comprising computing a function of semantic representations of the first and second text objects with an asymmetric vector space operator;
- an output component which outputs information based on the inference;
- and
- a processor which implements the components.
2 more elements
A method for making an entailment inference, comprising:
- storing an asymmetric vector space operator for computing a function of semantic representations of first and second text objects, the asymmetric vector space operator being selected from:
- a forward-inference entailment operator for predicting whether the first text object, having a semantic representation X is entailed by the second text object, having a semantic representation Y as a function of a dot product of X and log Y, or sigmoid functions thereof, where log Y is a vector in which each element is the loge of the corresponding element in Y;
- a backward-inference entailment operator for predicting whether the second text object entails the first text object as a function of a dot product of (1−Y) and log(1−X), or sigmoid functions thereof;
- and
- a factorized entailment operator for predicting whether the second text object entails the first text object as a function of a sum, over a set of k dimensions, of a log function of the kth elements of X and Y;
- with a processor, computing the selected asymmetric vector space operator to infer at least one of:
- whether the first text object entails the second text object,
- whether the second text object entails the first text object,
- a semantic representation of the second text object, given that an entailment relation exists between the first and second text objects;
- a semantic representation of the first text object, given that an entailment relation exists between the first and second text objects;
- and
- outputting information based on the inference.
9 more elements
Dependencies are inferred from the claim text.