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A method and system for constructing a hierarchical semantic tree for language understanding

A construction method and language understanding technology, applied in the field of hierarchical semantic tree construction methods and systems, can solve problems such as not necessarily ideal effects, strong domain dependence, and effect discounts, and achieve the effect of improving readability and accuracy

Inactive Publication Date: 2018-05-01
BEIJING NORMAL UNIVERSITY
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  • Description
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Problems solved by technology

The schema of the entity is defined in this scheme, which includes semantic type and probability, Markov probability, and semantic rules. The acquisition of these semantic content requires training of large-scale data, which is highly dependent on the domain of text. Due to the complexity of the task, The effect obtained may not be ideal, and all subsequent operations depend on the result of this step, and the effect will be greatly reduced

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  • A method and system for constructing a hierarchical semantic tree for language understanding
  • A method and system for constructing a hierarchical semantic tree for language understanding
  • A method and system for constructing a hierarchical semantic tree for language understanding

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Embodiment 1

[0047] Provide a kind of hierarchical semantic tree construction method and system for language comprehension in the present embodiment, semantic tree is the semantic structure tree, is for a sentence in natural language, refers to the feature word block (core verb) in a sentence lexical chunk) and the semantic relationship between other chunks determined by it. For example, the characteristic chunk V in a sentence is a verb expressing action, which determines that there must be actor chunks, object chunks, and content chunks in this sentence. Only in this way can the semantics of the sentence be complete. Although one of the latter three can be omitted in a certain context, these four chunks are the necessary components for the complete semantics of a sentence, and they are also called main chunks. In contrast, auxiliary language chunks are not necessary components for the establishment of a sentence, but mainly express the way, means, way, condition, time, etc. of an action....

Embodiment 2

[0077] A specific method for constructing a hierarchical semantic tree is given in this embodiment, and the basic flow of the scheme is also as follows figure 1 As shown, the method 100 for constructing a hierarchical semantic tree in this embodiment begins at step S110 by inputting the sentence to be processed, and then preprocessing the sentence to be processed in step S120, that is, performing word segmentation on the sentence to be processed according to the domain dictionary and the general dictionary, and loading Semantic knowledge of words, semantic knowledge mainly includes six generalized concept classes of words, namely V (dynamic), G (static), W (object), P (person), U (attribute), L (logic) and Several subcategories under its overall planning; secondly, in step S130, identify the semantic nodes of the statement and distinguish its levels, the first step is to use the LV rule to identify all semantic nodes to the result after word segmentation, the second step It is...

Embodiment 3

[0111] A specific application example is given in this embodiment, Figure 4 and Figure 5 is a diagram illustrating the result of building a hierarchical semantic tree for an example sentence. Such as Figure 4As shown, the sentence to be processed is "the web browser uses the uniform resource locator to send the HTML request to the server controlled by the system.", and the semantic tree structure at the clause level is: GBK1 "web browser" + ABK "use uniform resource The locator "+L0" sends the "+GBK2" HTML request "+EG" to "+GBK3" the server controlled by the system", wherein the CHK_SST (period) block serves as the root node. The semantic nodes of the first level are L1 (use), L0 (will), V (send to), all three levels are 0; the semantic edges of the first level are CHK_ABK (Use Uniform Resource Locator), CHK_L0 (will ), CHK_EG (sent to), CHK_GBK (web browser, HTML request, remote server), the six language block levels are all 0, and it hangs out as a child node of the r...

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Abstract

A method and system for constructing a hierarchical semantic tree for language understanding. The method mainly includes the following steps: segmenting sentences into words and loading a semantic knowledge base; identifying all nodes of the sentence according to the LV rule; The hierarchy of nodes; generate a special node for the punctuation at the end of the sentence as the root node of the semantic tree; merge it according to the node information generated above, identify the semantic edge block of the sentence, and hang the 0-level semantic edge as a child node on the root Node; loop through each of its child nodes until there are no low-level semantic edges, and hang on the child nodes as leaf nodes. In the absence of syntactic resources, the scheme only uses semantic information and word positions and collocations to obtain semantic structure trees, enabling computers to enter the deep semantic level of natural language, complete various processing of natural language on the basis of understanding, and realize It is the first step of natural language semantic understanding, which can be used for information retrieval, automatic summarization, machine translation, text classification and information filtering, etc.

Description

technical field [0001] The invention relates to the field of natural language processing, in particular to a method and a system for constructing a hierarchical semantic tree obtained by using semantic knowledge and the position and collocation of words. Background technique [0002] With the development of electronic information technology, digital information resources are widely used more and more. This requires that machines can also understand natural language, and complete various processing of natural language on the basis of "understanding", such as information retrieval, automatic summarization, machine translation, text classification, and information filtering. It can be seen that enabling computers to enter the semantic depth of natural language is a condition for achieving the above purpose. In order for a machine to understand the meaning of natural language, it must first understand the structure of natural language sentences. Sentence structure is a basic st...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/27
Inventor 晋耀红朱筠刘小蝶
Owner BEIJING NORMAL UNIVERSITY
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