Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method and device for labeling semantic role

A semantic role labeling and semantic representation technology, applied in the field of semantic role labeling methods and devices, can solve the problem of high cost and achieve the effect of reducing dimensions

Active Publication Date: 2015-03-25
BEIJING BAIDU NETCOM SCI & TECH CO LTD
View PDF2 Cites 33 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] (3) More than 90% of the time is spent on constructing sparse features, looking up tables, and calling classifiers, which is very costly

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method and device for labeling semantic role
  • Method and device for labeling semantic role
  • Method and device for labeling semantic role

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0029] figure 1 It is a schematic flowchart of a semantic role labeling method provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation where semantic role labeling is performed on sentences in application scenarios where semantic role labeling of sentences is required, such as automatic summary generation, knowledge mining, sentiment analysis, statistical machine translation, or search correlation calculation. The method can be executed by a semantic role tagging device, which is implemented by software and can be built into terminal devices such as smart phones, tablet computers, notebook computers, desktop computers or personal digital assistants. see figure 1 , the semantic role labeling method provided in this embodiment specifically includes the following operations:

[0030] Operation 110. Obtain at least one classification feature of the word segmentation in the target sentence to be labeled.

[0031] Operation 120, determine...

Embodiment 2

[0052] Figure 2A It is a schematic flowchart of a semantic role labeling method provided in Embodiment 2 of the present invention. On the basis of the first embodiment above, this embodiment further optimizes the task of "identifying the predicate in the target sentence" among the three tasks of semantic role labeling. see Figure 2A , the semantic role labeling method provided in this embodiment specifically includes the following operations:

[0053] Operation 210. Obtain at least one classification feature of the word segmentation in the target sentence to be labeled.

[0054] Operation 220, determine the acquired semantic representation information of each classification feature.

[0055] In operation 230, the semantic representation information of each classification feature is used as an input of a pre-generated first neural network classifier, and the first neural network classifier is used to identify whether the word segmentation is a predicate.

[0056] In this ...

Embodiment 3

[0093] Figure 3A It is a schematic flowchart of a semantic role labeling method provided in Embodiment 3 of the present invention. On the basis of the first embodiment above, this embodiment further optimizes the task of "identifying the semantic case of the predicate" among the three tasks of semantic role labeling. see Figure 3A, the semantic role labeling method provided in this embodiment specifically includes the following operations:

[0094] Operation 310. Obtain at least one classification feature of the predicate in the target sentence to be labeled.

[0095] Operation 320, determine the acquired semantic representation information of each classification feature.

[0096] In operation 330, the semantic representation information of each classification feature is used as an input of the pre-generated second neural network classifier, and the second neural network classifier is used to identify the semantic lattice of the predicate.

[0097] In this embodiment, th...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The embodiment of the invention discloses a method and device for labeling a semantic role. The method comprises the steps that at least one classification feature of a participle in an object statement to be labeled is acquired; semantic representation information of the acquired classification features is determined; semantic representation of all the classification features is adopted as input of a pre-generated neural network classifier, and semantic role labeling is carried out on the participle through the neural network classifier. According to the technical scheme, the complex and sparse feature based on a plurality of words, a plurality of word characteristics, a plurality of depending arc signs and a plurality of depending paths can be easily mapped into a dense feature, therefore, the dimension of feature space and feature establishment complexity are lowered, and a plurality of features can be combined automatically.

Description

technical field [0001] The embodiments of the present invention relate to the field of computer technology, and in particular to a semantic role labeling method and device. Background technique [0002] Semantic role labeling, as one of the mainstream methods for analyzing the semantic backbone of sentences, focuses on describing the structural information of sentences from a semantic perspective. important application value. [0003] At present, the input of the system for semantic role labeling is usually the sentence to be labeled, and the output is the semantic structure tree of the sentence. Among them, the semantic structure tree describes all the semantic roles of the predicates in the sentence and the category of each semantic role. In the prior art, after receiving a certain sentence, the system usually implements the semantic role labeling of the sentence through the following scheme: first extract the words, parts of speech, dependency arcs, dependency paths, an...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F17/27G06F17/30
Inventor 吴先超
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products