Abstract: According to an aspect, searching, recommending, and exploring documents through conceptual associations includes receiving a plurality of documents and extracting concepts from each of the documents. A degree of relation between each of the documents and concepts in a knowledge base is calculated. An aspect also includes, in response to receiving a query, determining one or more concepts from the query. For each of the concepts, a list of documents having a highest degree of relation to the concept is retrieved. An aspect also includes outputting a list that is responsive to the one or more retrieved lists.

Abstract: A sentence creation system, which outputs an opinion sentence on an agenda, includes: an input unit into which the agenda is input; an agenda analyzing unit analyzing the agenda and judging the polarity of the agenda and a keyword used for searching; a searching unit searching for articles using the keyword and a disputed point word showing a disputed point in the discussion; a disputed point determining unit for determining the disputed point used for creating the opinion sentence; a sentence extracting unit for extracting sentences in which the disputed point is described among the articles output by the searching unit; a sentence sorting unit for creating sentences by sorting the extracted sentences; an evaluating unit for evaluating the sentences; a paraphrasing unit for inserting appropriate conjunctions into the sentences; and an output unit for outputting the most highly evaluated sentence among the plural sentences as the opinion sentence.

Abstract: A method includes obtaining an input text, identifying a first term in the input text, and accessing lexicon data to identify a first entry corresponding to the first term. The first entry includes core data corresponding to domain-independent lexical information for the first term, and non-core data corresponding to domain-specific lexical information for the first term. The method also includes determining that the non-core data of the first entry identifies a second term in the input text as a modifier of the first term. The method further includes generating a partially parsed and bracketed version of the input text. The partially parsed and bracketed version indicates that the second term modifies the first term in the input text. The method also includes generating a parsed version of the input text based on the partially parsed and bracketed version of the input text.

Abstract: A system for generating video clips includes a video processing system configured to receive a video file from a video capture system, and to create video clips based on significant moments identified in the video file. The video processing system includes a file storage and database system configured to store the video file, and storing an ontology and keywords associated with themes that are pertinent to the overall theme of the video file. The video processing system also includes a natural language processing (NLP) moments module configured to identify themes contained in the video file using the ontology and the keywords, and to identify time codes associated with the identified themes. The video processing system also includes a video clip generator configured to generate video clips based on the identified time codes.

Abstract: An agent automation system includes a memory configured to store a natural language understanding (NLU) framework, and a processor configured to perform actions, including: generating a meaning representation from an annotated utterance tree of an utterance, wherein a structure of the meaning representation indicates a syntactic structure of the utterance and one or more subtree vectors of the meaning representation indicate a semantic meaning of one or more intent subtrees of the meaning representation; searching the meaning representation of the utterance against an understanding model to extract intents/entities of the utterance based on the one or more subtree vectors of the meaning representation, wherein the understanding model includes a plurality of meaning representations derived from the intent/entity model; and providing the intents/entities of the utterance to a reasoning agent/behavior engine (RA/BE) of the agent automation system that performs one or more actions in response to the intents/entit

Abstract: A speech recognition terminal includes: a voice input unit to accept an input of a voice; a speech recognition command unit to command a speech recognition unit to convert voices of joined voice data acquired by the voice input unit joining the voice data of the voice accepted by the voice input unit to the voice data of the voice accepted previously into character information of a first language at an interval of predetermined time; a translation command unit to command a translation unit to translate first character information of a first language into a second language whenever receiving the first character information of the first language converted by the voice recognition unit; and a display unit to display the first character information of the second language translated by the translation unit together with the first character information of the first language.

Abstract: Logic may adjust communications between customers. Logic may cluster customers into a first group associated with a first subset of synonyms and a second group associated with a second subset of the synonyms. Logic may associate a first tag with the first group and with each of the synonyms of the first subset. Logic may associate a second tag with the second group and with each of the synonyms of the second subset. Logic may associate one or more models with pairs of the groups. A first pair may comprise the first group and the second group. The first model associated with the first pair may adjust words in communications between the first group and the second group, based on the synonyms associated with the first pair, by replacement of words in a communication between customers of the first subset and customers of the second sub set.

Abstract: A communication device is arranged to transmit a character string that identifies the device. The character string comprises a plurality of substrings, each of which comprises a sequence of characters. A property of the device is identified using a data structure having multiple nodes, wherein each of a plurality of nodes stores a respective hash value. Each hash value corresponds to the hash value that would be generated by performing a hash function on the sequence of characters of each substring. The data structure comprises references between the plurality of nodes, and the references define a path through the data structure that identifies the device. A node on the path is associated with a property of the device.

Abstract: Systems and processes for operating a digital assistant using a hierarchical belief state are disclosed. In an example process, a user utterance of a dialog is received. A belief state for the dialog is determined. The belief state comprises a plurality of dialog slots. Each dialog slot of the plurality of dialog slots includes a respective marginal certainty for a concept or property represented by the respective dialog slot. A first dialog slot of the plurality of dialog slots further includes one or more joint certainties for one or more interpretations arising from the first dialog slot. Based on the marginal certainty of each dialog slot of the plurality of dialog slots and the one or more joint certainties of the first dialog slot, a policy action is selected from a plurality of candidate policy actions that correspond to the belief state. The selected policy action is performed.

Abstract: Logic may adjust communications between customers. Logic may cluster customers into a first group associated with a first subset of synonyms and a second group associated with a second subset of the synonyms. Logic may associate a first tag with the first group and with each of the synonyms of the first subset. Logic may associate a second tag with the second group and with each of the synonyms of the second subset. Logic may associate one or more models with pairs of the groups. A first pair may comprise the first group and the second group. The first model associated with the first pair may adjust words in communications between the first group and the second group, based on the synonyms associated with the first pair, by replacement of words in a communication between customers of the first subset and customers of the second sub set.

Abstract: A knowledge graph (KG) is generated and refined. The generated KG describes direct relationships between different words associated with a particular classification. Initially, a semantic data source, such as a lexical database, is accessed to identify words that are similarly grouped and express a distinct concept. A KG generator creates a sparse KG that provides a direct connection between a seed word and other words. The sparse KG is used by a dense KG generator to create a dense KG. The dense KG generator creates a dense KG that joins each of the different words directly with the seed word for the category. At different points during the creation and refinement of the KG, a user may add or remove one or more connections that affect the creation of the KG.

Abstract: The disclosure relates to transferred learning from a first language (e.g., a source language for which a semantic parser has been defined) to a second language (e.g., a target language for which a semantic parser has not been defined). A system may use knowledge from a trained model in one language to model another language. For example, the system may transfer knowledge of a semantic parser from a first (e.g., source) language to a second (e.g., target) language. Such transfer of knowledge may occur and be useful when the first language has sufficient training data but the second language has insufficient training data. The foregoing transfer of knowledge may extend the semantic parser for multiple languages (e.g., the first language and the second language).

Abstract: Ontologies are used to comprehend regular expressions, by selecting, based on a context relating to a domain of a regular expression, an ontology and an assertion base, parsing the regular expression to identify at least one fragment of the regular expression, identifying one or more assertions in the assertion base corresponding to one of the identified fragments, identifying, for each identified assertion, an associated node in the ontology, and returning, based on the associated nodes, a concept in the ontology as representing the associated fragment of the regular expression.

Abstract: A public speaking trainer has a computer system including a display monitor. A microphone is coupled to the computer system. A video capture device is coupled to the computer system. A biometric device is coupled to the computer system. A simulated environment including a simulated audience member is rendered on the display monitor using the computer system. A presentation is recorded onto the computer system using the microphone and video capture device. A first feature of the presentation is extracted based on data from the microphone and video capture device while recording the presentation. A metric is calculated based on the first feature. The simulated audience member is animated in response to a change in the metric. A score is generated based on the metric. The score is displayed on the display monitor of the computer system after recording the presentation. A training video is suggested based on the score.

Abstract: A system and method for accent invariant speech recognition comprising: maintaining a database scoring a set of language units in a given language, and for each of the language units, scoring audio samples of pronunciation variations of the language unit pronounced by a plurality of speakers; extracting and storing m the database a feature vector for locating each of the audio samples in a feature space; identifying pronunciation variation distances, which are distances between locations of audio samples of the same language unit in the feature space, and inter-unit distances, which are distances between locations of audio samples of different language units in the feature space; calculating a transformation applicable on the feature space to reduce the pronunciation variation distances relative to the inter-unit distances; and based on the calculated transformation, training a processor to classify as a same language unit pronunciation variations of the same language unit.

Abstract: Techniques for generating matchups of sale and coupon deals are described. For example, deal data that pertains to a sale deal and a coupon deal is received. A sale brand identification and a coupon brand identification are identified based on the deal data. A first set of deal data including the sale brand identification and corresponding to the sale deal, and a second set of deal data including the coupon brand identification and corresponding to a coupon deal are determined based on the deal data. A matchup of the sale deal and the coupon deal is generated based on matching the sale brand identification and the coupon brand identification, detecting a sale deal type in the first set of deal data and a coupon deal type in the second set of data, and determining that a sale deal's and a coupon deal's validity periods overlap and have not expired.

Abstract: In certain implementations, a system for facilitating voice commerce is provided. A user input comprising a natural language utterance related to a product or service to be purchased may be received. A first product or service that is to be purchased may be determined based on the utterance. First payment information that is to be used to purchase the first product or service may be obtained. First shipping information that is to be used to deliver the first product or service may be obtained. A purchase transaction for the first product or service may completed based on the first payment information and the first shipping information without further user input, after the receipt of utterance, that identifies a product or service type or a product or service, seller information, payment information, shipping information, or other information related to purchasing the first product or service.

Abstract: A contextual analysis engine systematically extracts, analyzes and organizes digital content stored in an electronic file such as a webpage. Content can be extracted using a text extraction module which is capable of separating the content which is to be analyzed from less meaningful content such as format specifications and programming scripts. The resulting unstructured corpus of plain text can then be passed to a text analytics module capable of generating a structured categorization of topics included within the content. This structured categorization can be organized based on a content topic ontology which may have been previously defined or which may be developed in real-time. The systems disclosed herein optionally include an input/output interface capable of managing workflows of the text extraction module and the text analytics module, administering a cache of previously generated results, and interfacing with other applications that leverage the disclosed contextual analysis services.

Abstract: A system for collecting elements as a basis for generating a social scenario useful to make a well-balanced good decision. A complex predicate template collecting apparatus includes: a simple predicate template DB storing simple predicate templates having positive or negative polarity values added; an object noun dictionary; a complex predicate template candidate extractor extracting complex predicate template candidates each formed of a combination of a word specified by the object noun dictionary and a simple predicate template, from a WEB archive; a sahen-noun polarity adder, a quantifier noun polarity adder and a trouble-noun polarity adder, determining polarity of a noun in each of the complex predicate template candidate; and a complex predicate template polarity calculator calculating polarity of a complex predicate template candidate by a combination of the polarity of the noun and the polarity of the simple predicate template included in the complex predicate template.

Abstract: Conversation-based context rules for altering virtual reality (VR) gaming and for switching between input languages based on heuristics related to past conversations between users.

Abstract: Systems, apparatuses, methods, and computer program products are disclosed for processing electronic information indicative of natural language. An example method includes receiving first electronic information indicative of a sequence of words provided by a user and identifying, based on the first electronic information, a first word and a first natural language. The example method further includes receiving second electronic information indicative of an exogenous event and identifying, based on the second electronic information, the exogenous event. The example method further includes generating one or more natural language attribute data sets based on the identified first word, first language, and exogenous event. The example method further includes generating a natural language transliteration data set based on the one or more natural language attribute data sets.

Abstract: A method for electronically utilizing content in a communication between a customer and a customer representative is provided. An audible conversation between a customer and a service representative is captured. At least a portion of the audible conversation is converted into computer searchable data. The computer searchable data is analyzed during the audible conversation to identify relevant meta tags previously stored in a data repository or generated during the audible conversation. Each meta tag is associated with the customer. Each meta tag provides a contextual item determined from at least a portion of one of a current or previous conversation with the customer. A meta tag determined to be relevant to the current conversation between the service representative and the customer is displayed in real time to the service representative currently conversing with the customer.

Abstract: Systems and processes for exemplar-based natural language processing are provided. In one example process, a first text phrase can be received. It can be determined whether editing the first text phrase to match a second text phrase requires one or more of inserting, deleting, and substituting a word of the first text phrase. In response to determining that editing the first text phrase to match the second text phrase requires one or more of inserting, deleting, and substituting a word of the first text phrase, one or more of an insertion cost, a deletion cost, and a substitution cost can be determined. A semantic edit distance between the first text phrase and the second text phrase in a semantic space can be determined based on one or more of the insertion cost, the deletion cost, and the substitution cost.

Abstract: A mechanism is disclosed for evaluating the quality of a machine translation system. Propositions are identified within a source language string and within a translation of the source language string generated by a machine translation system. The propositions can be identified using an automated mechanism or using human translators through the use of a human intelligence task site. Once the propositions have been identified, the propositions identified in the source language string can be compared to the propositions identified in the translated target language string. The results of the comparison can be utilized to compute a quality score for the translation. A final quality score can be generated for the machine translation system by repeating this process for multiple source language strings. The final quality score can then be utilized to improve the quality of models utilized by the machine translation system.

Abstract: Systems for distributed graph data management that use graph structures to model data and respond to different types of queries. Systems that provide analytic tools and machine learning based on graph structures. Systems for distributed graph data management that provide packaged solutions for different application areas.

Abstract: A processing method includes acquiring first parallel text data which is a pair of a first text described in a first language and a first translation of the first text into a second language; evaluating whether the first parallel text data has a possibility of mistranslation on the basis of words included in the first text and the first translation; and outputting information based on the evaluation result. It is evaluated whether the first parallel text data has a possibility of mistranslation on the basis of results of (1) a first determination as to whether the first text includes either or both of a word with a first meaning and an antonym of the word and (2) a second determination as to whether the first translation includes either or both of a translation word with the first meaning and an antonym of the translation word.

Abstract: A system and method for improving accuracy of natural language processing using a plurality of speech recognition engines, a data fusion model to identify a correct result from the plurality of speech recognition engines and a semantic understanding model, separate and distinct from the speech recognition model, to process the correct results. A corpus is developed using the correct results and the corpus is used to train the data fusion model and the semantic understanding model.

Abstract: Embodiments of the present invention provide methods, systems, apparatuses, and computer program products for aiding user access to technical data for an item. In one embodiment a method is provided comprising providing a model of the item, wherein the model comprises a plurality of visual representations, each visual representation representing one or more components of the item; receiving input selecting at least one of the one or more visual representations; responsive to receiving input selecting the at least one of the one or more visual representations, identifying one or more topics associated with the selected visual representation; providing at least a portion of the one or more topics associated with the selected visual representation; receiving input selecting at least one of the one or more topics; and responsive to receiving input selecting a topic of the one or more topics, providing technical data associated with the topic.

Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a cognitive natural language processing system. The cognitive natural language processing (NLP) system analyzes a portion of natural language text to identify an attribute specified in the natural language text. The cognitive NLP system analyzes the portion of natural language text to determine whether a known negation trigger is present in the natural language text in association with the attribute. In response to determining that the natural language text does not contain a known negation trigger in association with the attribute, the cognitive NLP system determines whether the attribute is negated based on instances of the attribute in other natural language content similar to the natural language text.

Abstract: Mechanisms are provided to perform embedding of content of a natural language document. The mechanisms receive a document data object of an electronic document and analyze a structure of the electronic document to identify one or more structural document elements that have a relationship with the document data object. A dependency data structure is generated, representing the electronic document, where edges define relationships between document elements and at least one edge represents at least one relationship between the one or more structural document elements and the document data object. The mechanisms embed the document data object based on the at least one relationship to thereby represent the document data object as a vector data structure. The mechanisms perform natural language processing on the portion of natural language content based on the vector data structure. The one or more structural document elements are non-local non-contiguous with the document data object.

Abstract: Embodiments are directed to a computer-implemented method for ranking a proximity of data sources with one or more reference entities, which may be authoritative entities. The method comprises identifying several data sources and one or more reference entities. For each of the identified reference entities a vector of terms representative of said each of the reference entities is obtained. For each data source of the identified data sources, terms from said each data source are selected, an array comprising the selected terms can be accordingly populated, and a term frequency of terms of the vector obtained for said each of the reference entities is determined, in said array. The term frequency corresponds to the number of occurrences of said each of the terms in said array. The method ranks a proximity of the identified data sources with each of the one or more reference entities.

Abstract: An advertisement translation device is a device for translating an advertisement text displayed in a display area of a predetermined size in advertisement content, and displaying the translated advertisement text in the display area. The advertisement translation device includes: an advertisement text obtainment unit which obtains the advertisement text; a linguistic information obtainment unit which obtains linguistic information indicating a target language into which the advertisement text is to be translated; a translation unit which create translated text candidates by translating the advertisement text into the target language indicated by the linguistic information; and a selection unit which selects and outputs as a translated text, at least one of the translated text candidates a full text of which is displayable in a predetermined character size in the display area.

Abstract: The program directs a computer processor to resolve an anaphor in electronic natural language text. The program detects a plurality of entities and an anaphor in a span of parsed natural language text comprising one or more sentences, and extracts pairs of related entities based on domain knowledge. The program constructs a set of tuples, wherein each tuple is a data type comprising an anaphor, an antecedent entity (AE) appearing before the anaphor in the span of parsed natural language text, and an entity (E) appearing after the anaphor in the span of parsed natural language text, wherein the anaphor refers to the AE and relates the AE to the E. The program resolves the anaphor by determining which entity in the plurality of entities the anaphor references, using the constructed set of tuples, and selecting an AE among one or more candidate AEs.

Abstract: Examples of techniques for the real-time capture and translation of human thoughts and ideas into structured patterns are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method may include capturing, by a processing device, unstructured data. The method may also include extracting key terms from the unstructured data. Additionally, the method may include assigning an attribute to at least one of the key terms. The method may further include generating, by the processing device, a structured pattern based on the key terms and the attributes.

Abstract: Mechanisms receive natural language content and analyze the natural language content to generate a parse tree data structure. The mechanisms process the parse tree data structure to identify one or more instances of candidate hypothetical spans in the natural language content. Hypothetical spans are terms or phrases indicative of a hypothetical statement. The mechanisms calculate, for each candidate hypothetical span, a confidence score value indicative of a confidence that the candidate hypothetical span is an actual hypothetical span based on a personalized hypothetical dictionary data structure associated with a source of the natural language content. The mechanisms perform an operation based on the natural language content.

Abstract: The present disclosure contemplates a variety of improved methods and systems for enabling set up of a variety of disparate IoT devices coupled to the framework and/or ambient operating system of an assistant device. The described solution includes a voice-driven assistant device setup process. An assistant device can determine the IoT devices in its physical environment and provide setup instructions to the user. The setup including determining voice activatable commands, device information and the adapter to allow the assistant device to operate the one or more IoT devices in response to user instructions.

Abstract: A method includes hierarchically identifying occurrences of some of the words in the set of sentences; creating a first index for each of some of the words based on the upper hierarchy of occurrences identified for each word; receiving input of a queried word; hierarchically identifying occurrences of the queried word in the set of sentences; creating a second index based on the upper hierarchy of occurrences identified for the queried word; comparing the first index and the second index to calculate an estimated value for the number of occurrences of a word in the neighborhood of the queried word; and calculating the actual value of the number of occurrences of a word in the neighborhood of the queried word based on an upper hierarchy and lower hierarchy of the occurrences on condition that the estimated value is equal to or greater than a predetermined number.

Abstract: The present teaching relates to automatic formality classification and transformation of online text items. In one example, a request is received for transforming a formality level of a text item in an online communication. A current formality level of the text item is obtained. The current formality level represents a current degree of formality of the text item. A target formality level is determined for the text item based on the request. The target formality level represents a targeted degree of formality for the text item. The text item having the current formality level is transformed to a transformed text item having the target formality level. The transformed text item has a same literal meaning as the text item. The transformed text item is provided as a response to the request.

Abstract: An apparatus has a network interface circuit to receive a source sentence from a network connected client device. A processor is connected to the network interface circuit. A memory is connected to the processor. The memory stores translation data and instructions executed by the processor. The instructions executed by the processor operate a neural machine translation system. A translation hypothesis is formed from a prefix of a target sentence comprising an initial sequence of target words supplied by a user through an interface. The hypothesis is generated by the neural machine translation system that performs a constrained prefix decoding that repeatedly predicts a next word from previous target words. A suffix of the target sentence comprising a final sequence of words corresponding to a final sequence of words in the source sentence is formed using a beam search that constrains translation to match the prefix.

Abstract: A system and method for monitoring conversations of a community of users to identify topics of interest is provided. A user community which is based partly on social networking connections relative to a first user is identified. Conversations involving at least one member of the identified user community are monitored. Based in part on an aggregated analysis of the monitored conversations, keywords are selected to present to the first user. The first user is then provided with a display in which the selected keywords associated with the user community are presented to the first user such that the first user can select a keyword to access content associated therewith.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, can aggregate content from one or more electronic publication documents. In one aspect, a method includes obtaining information including an index to content items of an electronic publication including a discrete package of received data that is stored locally, the content items being less than all content in the electronic publication received; retrieving, by a computer based on one or more criteria, two or more of the content items provided in disparate portions of the electronic publication, including the discrete package of received data, using the index; and presenting the two or more of the content items together on an output device in a user interface format different from that of the electronic publication.

Abstract: Systems and methods of automated ontology development include a corpus of communication data. The corpus of communication data includes communication data from a plurality of interactions and is processed. A plurality of terms are extracted from the corpus. Each term of the plurality is a plurality of words that identify a single concept within the corpus. An ontology is automatedly generated from the extracted terms.

Abstract: Systems and methods are disclosed for extracting structured relation information from Chinese clinical notes. Structured relation information in the form of entity-feature-value (EFV) triples is disclosed. The EFV triples may be used for advanced data abstraction. An ontology-driven method for data extraction is disclosed. The ontology-driven method may include lexical and syntactic analysis followed by semantic analysis to generate the EFV triples.

Abstract: A computer-implemented method for automatically generating passwords that comply with password restrictions may include (1) maintaining a database that stores password criteria for a plurality of websites, (2) determining that a user is accessing a website that requests creation of a password, (3) determining a set of password complexity rules for the website by querying the database that stores the password criteria, (4) using the set of password complexity rules to automatically generate the password for the website such that the password complies with the password criteria for the website, and (5) providing the password for use in the website that requested creation of the password. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A method and apparatus for training a neural network language model, and a method and apparatus for recognizing speech data based on a trained language model are provided. The method of training a language model involves converting, using a processor, training data into error-containing training data, and training a neural network language model using the error-containing training data.

Abstract: A display apparatus includes an input interface that receives a user input for selecting a channel, a tuner that receives a broadcast signal corresponding to the channel, a display that displays a content included in the broadcast signal, a storage configured to store channel information obtained from the broadcast signal, a communicator configured to communicate with an external apparatus, and a controller that selects a channel based on the user input, displays content corresponding to the changed channel on the display, acquires a channel number, a source ID and a channel name with respect to the channel, and transmits the channel number, the source ID and the channel name to a server.

Abstract: Systems and methods for content aggregation creation are disclosed herein. The system can include memory having a content database and an aggregation database. The system can include a user device having a first network interface and a first I/O subsystem. The system can include a server that can: provide content to the user device via a first electrical signal; receive a selection of a portion of the provided content from the user device via a second electrical signal; automatically extract sentences from the selected portion of the provided content via a natural language processor; automatically generate a parse tree for one of the automatically extracted sentences; identify noun phrases from the part of speech tags within the parse tree; place content associated with one of the noun phrase in a content aggregation; and output the content aggregation to the user device.

Abstract: A system for performing semantic search receives an electronic text corpus and separates the text corpus into a plurality of sentences. The system parses and converts each sentence into a sentence tree. The system receives a search query and matches the search query with one or more of the sentence trees.

Abstract: An auction apparatus according to the application includes a plan receiving unit and an auction providing unit. The plan receiving unit receives plan information indicating a plan of content from a content creator who creates the content. The auction providing unit presents the plan information received by the plan receiving unit and provides an auction service in which bid targets are a right to display an advertisement in an advertising space that is set to the content and a right to replace the advertisement displayed in the advertising space.

Abstract: In one implementation, a computer-implemented method for providing a graphical user interface (GUI) that teaches correct placement of accent marks on Spanish language words through a particular sequence of graphical elements includes receiving, through a GUI presented by a computing device, a selection of a graphical word element corresponding to a word to test as part of a Spanish language teaching program; identifying, by the computing device, a particular word set that corresponds to the word from among a plurality of word sets; and outputting, in the GUI presented by the computing device and based on the particular word set, a first graphical prompt element for the user to identify whether the word has a particular ending characteristic that corresponds to the particular word set.