# US 11,443,116 B2 · Electronic apparatus and control method thereof > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,443,116 B2 - Document ID: US11443116B2 - Status: Granted - Kind: B2 - Application number: 16/674,318 - Filed: 2019-11-05 - Published: 2020-05-07 - Granted: 2022-09-13 - Earliest claimed: 2018-11-05 - Assignees: Samsung Electronics Co., Ltd. - Applicants: Samsung Electronics Co., Ltd. - Inventors: Heejae Yu; Sejeong Kwon; Hwamin Kim - Web page: https://patentgrep.com/patent/US11443116B2 ## CPC - G06F 40/226: Validation - G06F 40/295: Named entity recognition - G06F 40/30: Semantic analysis - G06N 20/00: Machine learning - G06Q 50/10: Services - H04W 4/021: Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## Abstract An electronic apparatus is provided. The electronic apparatus includes a memory configured to store an entity identification model, and a processor configured to control the electronic apparatus to: identify a plurality of entities included in an input sentence input based on the entity identification model, acquire a search result corresponding to the plurality of entities, and correct and provide the input sentence based on the search result based on the plurality of entities not corresponding to the search result, wherein the entity identification model may be acquired by learning through an artificial intelligence algorithm to extract a plurality of sample entities included in each of a plurality of sample dialogues. At least a part of a method for identifying an entity from a dialogue may use an artificial intelligence model learned according to at least one of machine learning, a neural network, deep learning algorithm, or the like. ## Claims ### Claim 1 An electronic apparatus comprising: a memory configured to store an entity identification model; and a processor configured to control the electronic apparatus to: identify a plurality of entities included in an input sentence input based on the entity identification model, identify an attribute of each of the plurality of entities, acquire a search result corresponding to the plurality of entities, identify whether the plurality of entities corresponds to the search result based on the plurality of identified attributes, and based on the plurality of entities not corresponding to the search result, display a message indicating that the plurality of entities in the input sentence includes an error, wherein the entity identification model is acquired by learning through an artificial intelligence algorithm to extract a plurality of sample entities included in each of a plurality of sample dialogues. ### Claim 2 (depends on 1) The electronic apparatus of claim 1, wherein the message is a guide message for correcting the error. ### Claim 3 (depends on 1) The electronic apparatus of claim 1, wherein the processor is further configured to control the electronic apparatus to acquire a search result corresponding to at least two entities having different attributes. ### Claim 4 (depends on 1) The electronic apparatus of claim 1, wherein the processor is further configured to control the electronic apparatus to: acquire an importance for each of the plurality of entities based on a context of the input sentence, and identify whether a remaining entity among the plurality of entities corresponds to the search result for an entity having a highest importance among the plurality of entities. ### Claim 5 (depends on 1) The electronic apparatus of claim 1, wherein the processor is further configured to control the electronic apparatus to: identify a plurality of words included in the input sentence, and identify the plurality of entities among the plurality of words based on a context of the input sentence. ### Claim 6 (depends on 5) The electronic apparatus of claim 5, wherein the processor is further configured to control the electronic apparatus to: based on a second sentence subsequent to a first sentence among the input sentences being an affirmative sentence, identify a first word, among the plurality of words, identified in the first sentence as one of the plurality of entities. ### Claim 7 (depends on 5) The electronic apparatus of claim 5, wherein the processor is further configured to control the electronic apparatus to: based on a second sentence subsequent to a first sentence among the input sentences being a negative sentence, not use a first word, among the plurality of words, identified in the first sentence as the plurality of entities. ### Claim 8 (depends on 1) The electronic apparatus of claim 1, wherein the processor is further configured to control the electronic apparatus to: based on an error being present in the plurality of entities, correct the input sentence and provide the corrected input sentence. ### Claim 9 (depends on 1) The electronic apparatus of claim 1, wherein the processor is further configured to control the electronic apparatus to: based on a command being input, provide the plurality of entities used for acquiring the search result. ### Claim 10 A method of controlling an electronic apparatus, the method comprising: identifying a plurality of entities included in an input sentence input based on an entity identification model; identifying an attribute of each of the plurality of entities; acquiring a search result corresponding to the plurality of entities; identifying whether the plurality of entities corresponds to the search result based on the plurality of identified attributes, and based on the plurality of entities not corresponding to the search result, displaying a message indicating that the plurality of entities in the input sentence includes an error, wherein the entity identification model is obtained by learning through an artificial intelligence algorithm to extract a plurality of sample entities included in each of a plurality of sample dialogues. ### Claim 11 (depends on 10) The method of claim 10, wherein the message is a guide message for correcting the error. ### Claim 12 (depends on 10) The method of claim 10, wherein the acquiring comprises: acquiring a search result corresponding to at least two entities having different attributes. ### Claim 13 (depends on 10) The method of claim 10, wherein the method further comprises: acquiring an importance for each of the plurality of entities based on a context of the input sentence; and identifying whether a remaining entity among the plurality of entities corresponds to the search result for an entity having a highest importance among the plurality of entities. ### Claim 14 (depends on 10) The method of claim 10, wherein the identifying comprises: identifying a plurality of words included in the input sentence, and identifying the plurality of entities among the plurality of words based on a context of the input sentence. ### Claim 15 (depends on 14) The method of claim 14, wherein the identifying comprises: based on a second sentence subsequent to a first sentence among the input sentences being an affirmative sentence, identifying a first word, among the plurality of words, identified in the first sentence as one of the plurality of entities. ### Claim 16 (depends on 14) The method of claim 14, wherein the identifying comprises: based on a second sentence subsequent to a first sentence among the input sentences being a negative sentence, not using a first word, among the plurality of words, identified in the first sentence as the plurality of entities. ### Claim 17 (depends on 10) The method of claim 10, wherein the method further comprises: based on an error being present in the plurality of entities, correcting the input sentence and providing the corrected input sentence. ### Claim 18 (depends on 10) The method of claim 10, further comprising: based on a command being input, providing the plurality of entities used for acquiring the search result. ### Claim 19 (depends on 10) The method of claim 10, wherein the search result indicates locations of the plurality of entities and the association between each of the plurality of entities is satisfied when a distance between locations of the plurality of entities is less than a predetermined distance.