1. Articles in category: Parsing

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    1. Google SLING: An Open Source Natural Language Parser

      Google SLING: An Open Source Natural Language Parser

      Google SLING: An Open Source Natural Language Parser Written by Alex Armstrong Friday, 17 November 2017 Google Research has just released an open source project that might be of interest if you are into natural language processing. SLING is a combination of recurrent neural networks and frame based parsing. Natural language parsing is an important topic. You can get meaning from structure and parsing is how you get structure. It is important in processing both text and voice.

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    2. A Guide to Natural Language Processing (Part 1) AI

      A Guide to Natural Language Processing (Part 1) AI

      Parsing Documents We are going to talk about parsing in the general sense of analyzing a document and extracting its meaning. So, we are going to talk about the actual parsing of natural languages, but we will spend most of the time on other techniques. When it comes to understanding programming languages, parsing is the way to go. However, you can pick specific alternatives for natural languages.

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      Mentions: Russian NLP
    3. From 0 to 1 - Machine Learning, Nlp & Python-Cut to the Chase

      From 0 to 1 - Machine Learning, Nlp & Python-Cut to the Chase

      From 0 to 1 - Machine Learning, NLP & Python-Cut to the Chase From 0 to 1 - Machine Learning, NLP & Python-Cut to the Chase MP4 | Video: AVC 1280x720 | Audio: AAC 48KHz 2ch | Duration: 19 Hours 15M | 26.9 GB Genre: eLearning | Language: English This course is a down-to-earth, shy but confident take on machine learning techniques that you can put to work today. Let's parse that. The course is down-to-earth: it makes everything as simple as possible - but not simpler.

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    4. Image captioning with weak supervision

      Techniques for image captioning with weak supervision are described herein. In implementations, weak supervision data regarding a target image is obtained and utilized to provide detail information that supplements global image concepts derived for image captioning. Weak supervision data refers to noisy data that is not closely curated and may include errors. Given a target image, weak supervision data for visually similar images may be collected from sources of weakly annotated images, such as online social networks. Generally, images posted online include "weak" annotations in the form of tags, titles, labels, and short descriptions added by users. Weak supervision data ...

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    5. Automated generation and presentation of lessons via digital media content extraction

      An automated lesson generation learning system extracts text-based content from a digital programming file. The system parses the extracted content to identify a sentence, and key words within the sentences, to use as prompts in the lesson. The system also automatically generates a clip from the digital programming file, so that the clip is the portion of the file in which the sentence is spoken. The system then automatically generates and outputs a lesson containing the prompt and the clip.

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    6. In-context access of stored declarative knowledge using natural language expression

      Identifying a context for parsing a natural language expression. In an embodiment, a table comprising rows addressed according to context compartments is disclosed. Each compartment represents a context and comprises row(s), and each row represents a concept and comprises an outline field indicating an order of the concept in its context. Input expression(s) are received, and a first search is performed on the table to identify rows representing concepts corresponding to element(s) of the expression(s) and rows representing concepts corresponding to combinations of concepts represented by previously identified rows until a first row representing a higher-order ...

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    7. Method for identifying verifiable statements in text

      A method, system and computer-usable medium are disclosed for identifying verifiable statements in a corpus of text. A training corpus of text containing manually annotated instances of verifiable and non-verifiable statements is processed to parse the text into segmented statements, which are in turn processed to extract features. The extracted features and the annotated statements are then processed with a machine learning algorithm to generate a verifiable statement classification model. In turn, the verifiable statement classification model is referenced by a verifiable statement classification system to distinguish verifiable and non-verifiable statements contained within an input corpus of text.

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    8. Natural language dialogue method and natural language dialogue system

      A natural language dialog method and a natural language dialog system are provided. In the method, a first speech input is received and parsed to generate at least one keyword included in the first speech input, so that a candidate list including at least one report answer is obtained. According to a properties database, one report answer is selected from the candidate list, and a first speech response is output according to the report answer. Other speech inputs are received, and a user's preference data is captured from the speech inputs. The user's preference data is stored in ...

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    9. Dialog flow management in hierarchical task dialogs

      Methods and systems for managing multiple tasks using a dialog are presented. In some embodiments, a processor may parse a first natural language user input received at a user device to extract task related information from the first natural language user input. In response to identifying that the first natural language user input comprises a request to perform a first task, the processor may initiate execution of the first task. The user device may receive a second natural language user input after execution of the first task has been initiated which requests execution of a second task. The processor may ...

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    10. Dynamic source code generation

      Embodiments include method, systems and computer program products for dynamic source code generation. In some embodiments, a request comprising data may be received. Parsed natural language may be generated using the data. Knowledgebase data may be obtained. Source code may be generated based on the parsed natural language and the knowledgebase data. The generate source code may be transmitted in response to the request.

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    11. Syntactic parser assisted semantic rule inference

      Natural language understanding (NLU) engines perform better when they are trained with large amounts of data. However, a large amount of data is not always available. Embodiments of the present invention overcome this problem by generating annotated data for use in a NLU system. An example embodiment generates annotated data by parsing an input annotated phrase, generating a syntactic tree reflecting a grammatical structure of the parsed phrase, and generating one or more alternative versions of the input annotated phrase based on the syntactic tree. Alignment between expressions and corresponding annotations in the annotated phrase are preserved in the one ...

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    12. System and method for semantic processing of natural language commands

      A system, method and computer-readable storage devices are for processing natural language commands, such as commands to a robotic arm, using a Tag & Parse approach to semantic parsing. The system first assigns semantic tags to each word in a sentence and then parses the tag sequence into a semantic tree. The system can use statistical approach for tagging, parsing, and reference resolution. Each stage can produce multiple hypotheses, which are re-ranked using spatial validation. Then the system selects a most likely hypothesis after spatial validation, and generates or outputs a command. In the case of a robotic arm, the command ...

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    13. Method and apparatus for providing an anti-bullying service

      An approach is provided for an anti-bullying service. A service platform monitors interaction data from one or more applications, wherein the interaction data is associated with an interaction between a source and a target. The service platform analyzes the interaction data to parse one or more indicators of a monitored conduct between the source and the target. The service platform then initiates at least one of (a) a recording of the interaction data; (b) a transmission of an alert message, the one or more indicators, the interaction data, the monitored conduct, or a combination thereof to a third party; and ...

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    14. Optimizing parsing outcomes of documents

      A mechanism is provided for optimizing parsing of grammatical prose in a multi-prose electronic document. A received multi-prose electronic document is partitioned into a set of text segments of homogenous prose. A set of predefined Natural Language (NL) parsers is executed on each text segment in order to discern and measure a quality of parses by each NL parser throughout the multi-prose electronic document. A cross-parse analysis of the multi-prose electronic document and an aggregation of adjacent clauses or sentences of poor quality parses are performed. For each text segment, aggregation patterns yielding a best semantic role match are identified ...

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    15. Serving recurrent calendar events

      Computer-implemented systems and methods are provided for indexing and serving calendar event information. In accordance with some embodiments, information common to, and unique among, instances of a recurrent event may be determined. A markup document and search document including the common information and unique information may be generated, and a search index may be updated. Also, in accordance with some embodiments, a search query may be received and parsed, and recurrent event information can be scored as a possible search result.

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    16. Feature-based autocorrection

      A computing device is described that outputs for display at a presence-sensitive screen, a graphical keyboard having keys. The computing device receives an indication of a selection of one or more of the keys. Based on the selection the computing device determines a character string from which the computing device determines one or more candidate words. Based at least in part on the candidate words and a plurality of features, the computing device determines a spelling probability that the character string represents an incorrect spelling of at least one candidate word. The plurality of features includes a spatial model probability ...

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    17. Token-level interpolation for class-based language models

      Optimized language models are provided for in-domain applications through an iterative, joint-modeling approach that interpolates a language model (LM) from a number of component LMs according to interpolation weights optimized for a target domain. The component LMs may include class-based LMs, and the interpolation may be context-specific or context-independent. Through iterative processes, the component LMs may be interpolated and used to express training material as alternative representations or parses of tokens. Posterior probabilities may be determined for these parses and used for determining new (or updated) interpolation weights for the LM components, such that a combination or interpolation of component ...

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      Mentions: LMS
    18. Domain specific language design

      A computing system includes a processor; and a memory communicatively coupled to the processor. The processor is configured to: receive from a user, a number of annotations for at least one of a set of statements within a problem domain, the annotations identifying a set of elements within the statement; form a set of grammar rules for the problem domain based on the annotations; and parse the set of statements using the set of grammar rules.

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    19. Unsupervised Dependency Parsing without Gold Part-of-Speech Tags

      Valentin I. Spitkovsky, Hiyan Alshawi, Angel X. Chang, and Daniel Jurafsky. 2011. Unsupervised Dependency Parsing without Gold Part-of-Speech Tags. In Proceedings of the 2011 Conference on Empirical Methods on Natural Language Processing (EMNLP 2011).

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