CN109766549A - Temporal information extracting method, device and computer storage medium - Google Patents
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Abstract
A kind of temporal information extracting method, device and computer storage medium, which comprises obtain text data；The text data is split, entity word and the effective time in the text data are extracted；The entity word is matched with effective time, extracts the temporal information in the text data.Using the above method, the accuracy of the temporal information of extraction can be promoted.
Description
Technical field
The present invention relates to data processing fields more particularly to a kind of temporal information extracting method, device and computer to deposit
Storage media.
Background technique
Nowadays, in enterprise's exchange and the daily exchange of people, the information content in text data is very big.In various scenes
In, the temporal information in text data is very important objective information, therefore, is extracted from a large amount of text data accurate
Temporal information becomes particularly significant.
In the prior art, it is usually from the method for extracting time information in text data: extracts number from text data
Information, using digital information as temporal information.
However, directly using digital information as temporal information, the accuracy that will lead to the temporal information of extraction is lower.
Summary of the invention
Present invention solves the technical problem that be extract temporal information accuracy it is lower.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of temporal information extracting method, comprising: obtain text
Data；The text data is split, entity word and the effective time in the text data are extracted；By the reality
Pronouns, general term for nouns, numerals and measure words language is matched with effective time, extracts the temporal information in the text data.
Optionally, the entity word extracted in the text data and effective time, comprising: according to entity dictionary
Or meaning of a word parser extracts the entity word in the text data, extracts the information of the characterization number in the text data
As effective time.
Optionally, entity word in the text data is being extracted and after effective time, further includes: described in acquisition
In entity word with effective entity word of time correlation.
Optionally, the effective entity word obtained in the entity word with time correlation, comprising: according to entity word
Library or meaning of a word parser, in the text data, if there are tables within the scope of the default number of words that distance selectes entity word
The entity word for levying the time determines that the selected entity word is effective entity word.
Optionally, described to match entity word with effective time, the temporal information in the text data is extracted,
It include: that entity word effective time corresponding with the entity word is matched, is obtained according to the meaning of a word of entity word
To time information unit；According to position of the entity word in multiple temporal information units in the text data
The temporal information unit is formed temporal information by incidence relation and time sequencing incidence relation.
Optionally, the entity word according in multiple temporal information units is in the text data
Position incidence relation and time sequencing incidence relation, comprising: by regular expression, determine multiple temporal information units
In position incidence relation of the entity word in the text data.
Optionally, after the temporal information extracted in the text data, further includes: according to standard time lattice
Formula exports the temporal information.
The present invention also provides a kind of temporal information extraction elements, comprising: acquiring unit, split cells and extraction unit,
In: the acquiring unit, for obtaining text data；The split cells is extracted for splitting to the text data
Entity word and effective time in the text data；The extraction unit, for by the entity word and it is effective when
Between matched, extract the temporal information in the text data.
The present invention also provides a kind of computer readable storage mediums, are stored thereon with computer instruction, the computer can
Reading storage medium is non-volatile memory medium or non-transitory storage media, and the computer instruction executes any of the above-described when running
The step of temporal information extracting method of kind.
The present invention also provides a kind of electronic equipment, including memory and processor, computer is stored on the memory
The step of instruction, the processor executes any of the above-described kind of temporal information extracting method when the computer instruction is run.
Compared with prior art, the technical solution of the embodiment of the present invention has the advantages that
By obtaining text data, entity word and the effective time in the text data are extracted, by entity word
It is matched with effective time, obtains temporal information and extract rule, rule is extracted according to the temporal information, extracts detection data
In temporal information.Entity word is matched with effective time, some invalid digital informations can be filtered out, simultaneously because real
Pronouns, general term for nouns, numerals and measure words language itself includes the meaning of a word, can relatively accurately be matched with digital information, and then promotes the temporal information extracted
Accuracy.
Detailed description of the invention
Fig. 1 is the flow diagram of the temporal information extracting method provided in the embodiment of the present invention；
Fig. 2 is the structural schematic diagram of the temporal information extraction element provided in the embodiment of the present invention.
Specific embodiment
In the prior art, it is usually from the method for extracting time information in text data: extracts number from text data
Information, using digital information as temporal information.
However, directly using digital information as temporal information, the accuracy that will lead to the temporal information of extraction is lower.
In the embodiment of the present invention, by obtaining text data, entity word in the text data and effectively is extracted
Entity word is matched with effective time, extracts the temporal information in the text data by the time.By entity word with have
The effect time matches, and can filter out some invalid digital informations, simultaneously because entity word itself includes the meaning of a word, it can be more
It is accurately matched with digital information, and then promotes the accuracy for the temporal information extracted.
It is understandable to enable above-mentioned purpose of the invention, feature and beneficial effect to become apparent, with reference to the accompanying drawing to this
The specific embodiment of invention is described in detail.
It refering to fig. 1, is the flow diagram of the temporal information extracting method provided in the embodiment of the present invention, wherein specifically
Step are as follows:
S101 obtains text data.
In specific implementation, text data may include the data that Word document, Mail Contents etc. include text.
In specific implementation, available text data relevant to a certain user.Since the text of independent part is write
Be accustomed to it is relatively fixed, therefore when the text data of extraction is related to a certain user, the accuracy of the temporal information of extraction compared with
It is high.
In specific implementation, different according to the scene of application time information extraction, different types of textual data can be extracted
According to.For example, the extracting time information in the case where table fills in scene, the relevant text data of available table；For another example, postal is being write
Extracting time information under part scene, the relevant text data of available mail.Due to the text in different types of text data
Word sequential write is similar, therefore, different according to the scene of application time information extraction, extracts different types of text data,
The accuracy of the temporal information of extraction can be promoted.
S102 splits the text data, extracts entity word and effective time in the text data.
In specific implementation, text data can be split by meaning of a word parser or dictionary, will be expressed not
Same intension, understanding, evaluation or event paragraph or sentence be split, carried out in part after singulation entity word with
And the extraction of effective time, convenient for the extraction of subsequent temporal information.
In specific implementation, the entity word can be word that the time is characterized with written form, such as this year, bright
The words such as year, time, last month, the beginning of the month, tomorrow, today, afternoon.
In specific implementation, according to the application time information extracting method under different scenes, or the reality according to user
The object of setting, the entity word of extraction can be different.For example, being set according to user, entity word " year " is not extracted, is only extracted
Entity word " moon ", " day ", " when " etc..
In specific implementation, the effective time can be the word using number as the form of expression, for example, 2018,
2019, the words such as 12,19.
In specific implementation, according to the application time information extracting method under different scenes, or the reality according to user
Setting, the object of the effective time of extraction can not only include the sentence using numerical character as the form of expression.For example, word
" next ", according to meaning of a word parser or dictionary, " next " can be directed toward one specific digital " 18 ", therefore, " next "
Can also be used as effective time extracts, can with entity word " when ", makeup time information " when 18 ".
Step S103 matches the entity word with effective time, extracts the time letter in the text data
Breath.
In specific implementation, entity word can be matched with effective time according to the semanteme of entity word.For example,
Entity word " year " can match it with the effective time " 2018 " comprising continuous four numerical characters, when obtaining
Between information " 2018 ".
In specific implementation, entity word can will be matched with effective time according to dictionary.For example, being wrapped in dictionary
Containing " December ", there are entity word " moon " in text data, there are effective times near the entity word " moon "
Entity word " moon " can be matched with effective time " 12 ", obtain temporal information " December " by " 12 ".
In specific implementation, according to the expression-form of time, can extract utmostly meet temporal expressions form when
Between information.For example, after obtaining " 2018 " and " December ", in the expression-form of time, Nian Yuyue is continuously carry out table
It reaches, therefore available temporal information " in December, 2018 ".And so on, " Wednesday on December 19th, 2018 can be extracted
30 divide when the morning 8 " as temporal information.
In specific implementation, during entity word and effective time are carried out matched, a part can be filtered out simultaneously
It is not used in entity word and the effective time of characterization time.For example, include entity word " year " in word " A fall of seasonable snow gives promise of a fruitful year ", but
It is that this word itself does not indicate the time.In practical applications, certain numerical characters only indicate quantity, do not indicate the time.For example,
Numerical character in 1 grade 2 classes is not offered as the time.Therefore, during entity word and effective time are carried out matched,
The accuracy of temporal information extraction can be promoted by filtering out this part entity word and effective time.
In the embodiment of the present invention, the entity word in the text data is extracted according to entity dictionary or meaning of a word parser
Language extracts the information of the characterization number in the text data as effective time.
In specific implementation, the composition of entity word can be set by user according to practical application scene.Extract with it is described
The entity word that word in entity word matches.
In specific implementation, meaning of a word parser can be stammerer (jieba) segmentation methods, can also be by user according to reality
Border application scenarios are set as other algorithms for meaning of a word analysis.
In the embodiment of the present invention, effective entity word in the entity word with time correlation is obtained.
In specific implementation, not all entity word is all used for expression time information in the text data, or
The time of person's expression is more fuzzy, it is difficult to specific temporal information is determined, for example, entity word " season ".
In the embodiment of the present invention, according to entity dictionary or meaning of a word parser, in the text data, if being selected in distance
Determine the entity word that there is the characterization time within the scope of the default number of words of entity word, determines that the selected entity word has described in being
Imitate entity word.
In specific implementation, the selection range that number of words range is used to limit entity word is preset, temporal information is promoted and extracts
Accuracy.
In specific implementation, presetting number of words range can be set by user according to practical application scene.
For example, there is the entity word " day " of characterization time in selected entity word " moon ", thus within the scope of default number of words
Selected entity word " moon " can be regard as effective entity word.It is possible thereby to filter out the entity word of a part of not expression time
The excessively fuzzy entity word with portion of time expression.
It is according to the meaning of a word of entity word, the entity word is corresponding with the entity word in the embodiment of the present invention
Effective time is matched, and temporal information unit is obtained；Existed according to the entity word in multiple temporal information units
Position incidence relation and time sequencing incidence relation in the text data believe the temporal information unit makeup time
Breath.
In the embodiment of the present invention, by regular expression, the entity word in multiple temporal information units is determined
Position incidence relation of the language in the text data.
For example, entity word " year " matched to obtain temporal information unit " 2018 ", entity word with effective time " 2018 "
Language " moon " matches to obtain temporal information unit " December " with effective time " 12 ", and entity word " day " is matched with effective time " 20 "
Temporal information unit " 20 days " are obtained, entity word " morning " matches to obtain " when the morning 11 " with effective time " 11 ".
In specific implementation, there is time sequencing incidence relations between entity word, usually with " year-month-day-when-
Point " such sequence arranges.Secondly, by position incidence relation of the entity word in the text data, when determining a plurality of
Between information unit be for characterize a specific time.For example, a plurality of temporal information unit in a certain specific sentence is total
With the specific time expressed by direction statement author.
For example, temporal information unit is " 2018 ", " December ", " 20 days " and " morning 11 ", exist meeting entity word
Under conditions of position incidence relation and time sequencing incidence relation in the text data, it can be obtained with makeup time information
" when the December in 2018 of the morning 11 on the 20th ".
In the embodiment of the present invention, according to standard time format, the temporal information is exported.
For example, temporal information is " when the December in 2018 of the morning 11 on the 20th ", it is according to standard time format output
" 2018.12.20/11:00 ".
In specific implementation, standard time format can be set by user according to practical application scene, can improve user
Usage experience.
Referring to Fig.2, it is the structural schematic diagram of the temporal information extraction element 20 provided in the embodiment of the present invention, it is specific to wrap
It includes: acquiring unit 201, split cells 202 and extraction unit 203, in which:
The acquiring unit 201, for obtaining text data；
The split cells 202 extracts the entity word in the text data for splitting to the text data
Language and effective time；
The extraction unit 203 extracts the text data for matching the entity word with effective time
In temporal information.
In specific implementation, entity word is matched with effective time, some invalid digital informations can be filtered out, together
When since entity word itself includes the meaning of a word, can relatively accurately be matched with digital information, so promoted extract when
Between information accuracy.
In specific implementation, different according to the scene of application time information extraction, different types of textual data can be extracted
According to.For example, the extracting time information in the case where table fills in scene, the relevant text data of available table；For another example, postal is being write
Extracting time information under part scene, the relevant text data of available mail.Due to the text in different types of text data
Word sequential write is similar, therefore, different according to the scene of application time information extraction, extracts different types of text data,
The accuracy of the temporal information of extraction can be promoted.
In the embodiment of the present invention, the split cells 202 further include: extract subelement, the extraction subelement can be with
For extracting the entity word in the text data according to entity dictionary or meaning of a word parser, extract in the text data
Characterization number information as effective time.
In specific implementation, the composition of entity word can be set by user according to practical application scene.Extract with it is described
The entity word that word in entity word matches.
In specific implementation, meaning of a word parser can be stammerer (jieba) segmentation methods, can also be by user according to reality
Border application scenarios are set as other algorithms for meaning of a word analysis.
In the embodiment of the present invention, the split cells 202 further include: obtain subelement, the acquisition subelement can be with
For obtaining effective entity word in the entity word with time correlation.
In specific implementation, not all entity word is all used for expression time information in the text data, or
The time of person's expression is more fuzzy, it is difficult to determine specific temporal information, filter out this part entity word, can promote extraction
The accuracy of temporal information.
In the embodiment of the present invention, the split cells 202 further include: choose subelement, the selection subelement can be with
For according to entity dictionary or meaning of a word parser, in the text data, if selecting the predetermined word of entity word in distance
There is the entity word of characterization time in number range, determines that the selected entity word is effective entity word.
In specific implementation, the selection range that number of words range is used to limit entity word is preset, temporal information is promoted and extracts
Accuracy.
In specific implementation, presetting number of words range can be set by user according to practical application scene.
For example, there is the entity word " day " of characterization time in selected entity word " moon ", thus within the scope of default number of words
Selected entity word " moon " can be regard as effective entity word.It is possible thereby to filter out the entity word of a part of not expression time
The excessively fuzzy entity word with portion of time expression.
In the embodiment of the present invention, the extraction unit 203 further include: coupling subelement, the coupling subelement can be with
For the meaning of a word according to entity word, entity word effective time corresponding with the entity word is matched, is obtained
To time information unit；According to position association of the entity word in multiple temporal information units in the text data
Relationship and time sequencing incidence relation, by temporal information unit makeup time information.
In specific implementation, first extracting time information unit, then temporal information unit is formed into temporal information, due to the time
The composition of information unit is relatively simple, and the result precision extracted is high, therefore again believes temporal information unit makeup time
Breath, it is ensured that the accuracy of temporal information.
For example, entity word " year " matched to obtain temporal information unit " 2018 ", entity word with effective time " 2018 "
Language " moon " matches to obtain temporal information unit " December " with effective time " 12 ", and entity word " day " is matched with effective time " 20 "
Temporal information unit " 20 days " are obtained, entity word " morning " matches to obtain " when the morning 11 " with effective time " 11 ".
In specific implementation, there is time sequencing incidence relations between entity word, usually with " year-month-day-when-
Point " such sequence arranges.Secondly, by position incidence relation of the entity word in the text data, when determining a plurality of
Between information unit be for characterize a specific time.For example, a plurality of temporal information unit in a certain specific sentence is total
With the specific time expressed by direction statement author.
For example, temporal information unit is " 2018 ", " December ", " 20 days " and " morning 11 ", exist meeting entity word
Under conditions of position incidence relation and time sequencing incidence relation in the text data, it can be obtained with makeup time information
" when the December in 2018 of the morning 11 on the 20th ".
In the embodiment of the present invention, the extraction unit 203 further include: position enquiring subelement, position enquiring are single
Member can be also used for determining the entity word in multiple temporal information units in the text data by regular expression
In position incidence relation.
In the embodiment of the present invention, the extraction unit 203 further include: output subelement, the output subelement can be with
For according to standard time format, the temporal information to be exported.
In specific implementation, standard time format can be set by user according to practical application scene, can improve user
Usage experience.
For example, temporal information is " when the December in 2018 of the morning 11 on the 20th ", it is according to standard time format output
“2018.12.20/11.00”。
In the embodiment of the present invention, a kind of computer readable storage medium is also provided, is stored thereon with computer instruction, it is described
Computer readable storage medium is non-volatile memory medium or non-transitory storage media, and the computer instruction executes when running
The step of temporal information extracting method of any of the above-described embodiment.
It should be noted that can be used as a software module according to the temporal information extraction element of the embodiment of the present application
And/or hardware module and be integrated into electronic equipment, in other words, which may include the temporal information extraction element.
For example, the temporal information extraction element can be a software module in the operating system of the electronic equipment, or can be
It is directed to its application program developed；Certainly, which equally can be the crowd of the electronic equipment
One of more hardware modules.
In another embodiment of the application, the temporal information extraction element and the electronic equipment are also possible to discrete equipment
(for example, server), and the temporal information extraction element can be connected to the electronics by wired and or wireless network and set
It is standby, and interactive information is transmitted according to the data format of agreement.
In the electronic equipment that one embodiment of the application provides, comprising: one or more processors and memory；And it deposits
The computer program instructions of storage in memory, it is as above that computer program instructions execute processor
State the temporal information extracting method of any embodiment.
Processor can be central processing unit (CPU) or with data-handling capacity and/or instruction execution capability
The processing unit of other forms, and can control the other assemblies in electronic equipment to execute desired function.
Memory may include one or more computer program products, and the computer program product may include various
The computer readable storage medium of form, such as volatile memory and/or nonvolatile memory.The volatile memory
It such as may include random access memory (RAM) and/or cache memory (cache) etc..The non-volatile memories
Device for example may include read-only memory (ROM), hard disk, flash memory etc..It can store on the computer readable storage medium
One or more computer program instructions, processor can run described program instruction, to realize the application's described above
Step and/or other desired functions in the temporal information extracting method of each embodiment.Described computer-readable
The information such as the position of light intensity, compensation luminous intensity, optical filter can also be stored in storage medium.
In one example, electronic equipment can also include: input unit and output device, these components pass through total linear system
The interconnection of the bindiny mechanism of system and/or other forms.
The output device can be output to the outside various information, such as may include such as display, loudspeaker, printing
Machine and communication network and its remote output devices connected etc..
In addition to this, according to concrete application situation, electronic equipment can also include any other component appropriate.
Other than the above method and equipment, embodiments herein can also be computer program product, including calculate
Machine program instruction, computer program instructions make processor execute the time such as above-mentioned any embodiment when being run by processor
Step in information extracting method.
Computer program product can be write with any combination of one or more programming languages for executing sheet
Apply for the program code of embodiment operation, described program design language includes object oriented program language, such as Java,
C++ etc. further includes conventional procedural programming language, such as " C " language or similar programming language.Program code
It can fully execute on the user computing device, partly execute, held as an independent software package on a user device
Part executes on a remote computing or completely in remote computing device or service on the user computing device for row, part
It is executed on device.
In addition, embodiments herein can also be computer readable storage medium, it is stored thereon with computer program and refers to
It enables, the computer program instructions make the processor execute the above-mentioned temporal information of this specification to mention when being run by processor
It takes described in method part according to the step in the temporal information extracting method of the various embodiments of the application.
The computer readable storage medium can be using any combination of one or more readable mediums.Readable medium can
To be readable signal medium or readable storage medium storing program for executing.Readable storage medium storing program for executing for example can include but is not limited to electricity, magnetic, light, electricity
Magnetic, the system of infrared ray or semiconductor, device or device, or any above combination.Readable storage medium storing program for executing it is more specific
Example (non exhaustive list) includes: the electrical connection with one or more conducting wires, portable disc, hard disk, random access memory
Device (RAM), read-only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc
Read-only memory (CD-ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.
Although present disclosure is as above, present invention is not limited to this.Anyone skilled in the art are not departing from this
It in the spirit and scope of invention, can make various changes or modifications, therefore protection scope of the present invention should be with claim institute
Subject to the range of restriction.
Claims (10)
1. a kind of temporal information extracting method characterized by comprising
Obtain text data；
The text data is split, entity word and the effective time in the text data are extracted；
The entity word is matched with effective time, extracts the temporal information in the text data.
2. temporal information extracting method according to claim 1, which is characterized in that described to extract in the text data
Entity word and effective time, comprising:
The entity word in the text data is extracted according to entity dictionary or meaning of a word parser, is extracted in the text data
Characterization number information as effective time.
3. temporal information extracting method according to claim 2, which is characterized in that extracting the reality in the text data
Pronouns, general term for nouns, numerals and measure words language and after effective time, further includes:
Obtain effective entity word in the entity word with time correlation.
4. temporal information extracting method according to claim 3, which is characterized in that it is described obtain in the entity word with
Effective entity word of time correlation, comprising:
According to entity dictionary or meaning of a word parser, in the text data, if selecting the predetermined word of entity word in distance
There is the entity word of characterization time in number range, determines that the selected entity word is effective entity word.
5. temporal information extracting method according to claim 1, which is characterized in that described by the entity word and effective
Time is matched, and the temporal information in the text data is extracted, comprising:
According to the meaning of a word of entity word, entity word effective time corresponding with the entity word is matched, is obtained
To time information unit；
According to position incidence relation of the entity word in multiple temporal information units in the text data with
And time sequencing incidence relation, the temporal information unit is formed into temporal information.
6. temporal information extracting method according to claim 5, which is characterized in that described according to multiple temporal informations
Position incidence relation and time sequencing incidence relation of the entity word in the text data in unit, comprising:
By regular expression, determine the entity word in multiple temporal information units in the text data
Position incidence relation.
7. temporal information extracting method according to claim 1, which is characterized in that extracted in the text data described
Temporal information after, further includes:
According to standard time format, the temporal information is exported.
8. a kind of temporal information extraction element characterized by comprising acquiring unit, split cells and extraction unit, in which:
The acquiring unit, for obtaining text data；
The split cells, for being split to the text data, extract entity word in the text data and
Effective time；
The extraction unit, for the entity word to be matched with effective time, extract in the text data when
Between information.
9. a kind of computer readable storage medium, is stored thereon with computer instruction, the computer readable storage medium is non-
Volatile storage medium or non-transitory storage media, which is characterized in that the computer instruction run when perform claim require 1~
The step of 7 described in any item temporal information extracting methods.
10. a kind of electronic equipment, including memory and processor, it is stored with computer instruction on the memory, feature exists
In the computer instruction 1~7 described in any item temporal information extracting methods of processor perform claim requirement when running
The step of.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110222346A (en) * | 2019-06-20 | 2019-09-10 | 贵州电网有限责任公司 | A method of extracting effective time from interaction data |
| CN110245354A (en) * | 2019-06-20 | 2019-09-17 | 贵州电网有限责任公司 | The method of entity is extracted in a kind of schedule information |
| CN113032586A (en) * | 2021-03-19 | 2021-06-25 | 京东数字科技控股股份有限公司 | Method and device for extracting time information in text and electronic equipment |
| CN113723073A (en) * | 2021-07-12 | 2021-11-30 | 大箴(杭州)科技有限公司 | Corpus processing method and device, electronic equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105224601A (en) * | 2015-08-31 | 2016-01-06 | 小米科技有限责任公司 | A kind of method and apparatus of extracting time information |
| CN105718447A (en) * | 2014-12-05 | 2016-06-29 | 中兴通讯股份有限公司 | Time information extracting method and apparatus, and smart question and answer system |
| US20170315986A1 (en) * | 2016-04-28 | 2017-11-02 | International Business Machines Corporation | Cross-lingual information extraction program |
| CN107329948A (en) * | 2017-05-23 | 2017-11-07 | 努比亚技术有限公司 | Sentence describes time of origin presumption method, equipment and the storage medium of event |
-
2018
- 2018-12-29 CN CN201811643638.1A patent/CN109766549A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105718447A (en) * | 2014-12-05 | 2016-06-29 | 中兴通讯股份有限公司 | Time information extracting method and apparatus, and smart question and answer system |
| CN105224601A (en) * | 2015-08-31 | 2016-01-06 | 小米科技有限责任公司 | A kind of method and apparatus of extracting time information |
| US20170315986A1 (en) * | 2016-04-28 | 2017-11-02 | International Business Machines Corporation | Cross-lingual information extraction program |
| CN107329948A (en) * | 2017-05-23 | 2017-11-07 | 努比亚技术有限公司 | Sentence describes time of origin presumption method, equipment and the storage medium of event |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110222346A (en) * | 2019-06-20 | 2019-09-10 | 贵州电网有限责任公司 | A method of extracting effective time from interaction data |
| CN110245354A (en) * | 2019-06-20 | 2019-09-17 | 贵州电网有限责任公司 | The method of entity is extracted in a kind of schedule information |
| CN113032586A (en) * | 2021-03-19 | 2021-06-25 | 京东数字科技控股股份有限公司 | Method and device for extracting time information in text and electronic equipment |
| CN113032586B (en) * | 2021-03-19 | 2023-11-03 | 京东科技控股股份有限公司 | Method and device for extracting time information in text and electronic equipment |
| CN113723073A (en) * | 2021-07-12 | 2021-11-30 | 大箴(杭州)科技有限公司 | Corpus processing method and device, electronic equipment and storage medium |
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Application publication date: 20190517 |