1. Articles in category: Parsing

    49-72 of 598 « 1 2 3 4 5 6 ... 23 24 25 »
    1. Shallow Parsing Pipeline for Hindi-English Code-Mixed Social Media Text. (arXiv:1604.03136v1 [cs.CL])

      In this study, the problem of shallow parsing of Hindi-English code-mixed social media text (CSMT) has been addressed. We have annotated the data, developed a language identifier, a normalizer, a part-of-speech tagger and a shallow parser. To the best of our knowledge, we are the first to attempt shallow parsing on CSMT. The pipeline developed has been made available to the research community with the goal of enabling better text analysis of Hindi English CSMT.

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    2. A Fast Unified Model for Parsing and Sentence Understanding. (arXiv:1603.06021v1 [cs.CL])

      Tree-structured neural networks exploit valuable syntactic parse information as they interpret the meanings of sentences. However, they suffer from two key technical problems that make them slow and unwieldy for large-scale NLP tasks: they can only operate on parsed sentences and they do not directly support batched computation.

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      Mentions: NLP
    3. Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations. (arXiv:1603.04351v1 [cs.CL])

      We present a simple and effective scheme for dependency parsing which is based on bidirectional-LSTMs (BiLSTMs). Each sentence token is associated with a BiLSTM vector representing the token in its sentential context, and feature vectors are constructed by concatenating a few BiLSTM vectors. The BiLSTM is trained jointly with the parser objective, resulting in very effective feature extractors for parsing.

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    4. Easy-First Dependency Parsing with Hierarchical Tree LSTMs. (arXiv:1603.00375v1 [cs.CL])

      We suggest a compositional vector representation of parse trees that relies on a recursive combination of recurrent-neural network encoders. To demonstrate its effectiveness, we use the representation as the backbone of a greedy, bottom-up dependency parser, achieving state-of-the-art accuracies for English and Chinese, without relying on external word embeddings. The parser's implementation is available for download at the first author's webpage.

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    5. Caching of deep structures for efficient parsing

      A parsing method and system. The method includes generating an n-gram model of a domain and computing a tf-idf frequency associated with n-grams of the n-gram model. A list including a frequently occurring group of n-grams based on the tf-idf frequency is generated. The frequently occurring group of n-grams is transmitted to a deep parser component and a deep parse output from the deep parser component is generated. The deep parse output is stored within a cache and a processor verifies if a specified text word sequence of the deep parse output is available in the cache.

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    6. Recurrent Neural Network Grammars. (arXiv:1602.07776v1 [cs.CL])

      We introduce recurrent neural network grammars, probabilistic models of sentences with explicit phrase structure. We explain efficient inference procedures that allow application to both parsing and language modeling. Experiments show that they provide better parsing in English than any single previously published supervised generative model and better language modeling than state-of-the-art sequential RNNs in English and Chinese.

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    7. Generation of a semantic model from textual listings

      A corpus of textual listings is received and main concept words and attribute words therein are identified via an iterative process of parsing listings and expanding a semantic model. During the parsing phase, the corpus of textual listings is parsed to tag one or more head noun words and/or one or more identifier words in each listing based on previously identified main concept words or using a head noun identification rule. Once substantially each listing in the corpus has been parsed in this manner, the expansion phase assigns head noun words as main concept words and modifier words as ...

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    8. System and method for extracting ontological information from a body of text

      A system for extracting ontological information from a body of text is disclosed. The system parses one or more sentences from the body of text into parse tree format to generate a set of parsed sentences. The system further performs named-entity-recognition by identifying a subset of parsed sentences from the set of parsed sentences. A subset of noun phrases from the subset of parsed sentences are identified and the noun phrases are examined to classify the noun phrases as an entity or as a property. The system also identifies and outputs a conceptual relationship between the entity and the property ...

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    9. Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing. (arXiv:1601.06068v1 [cs.CL])

      One of the limitations of semantic parsing approaches to open-domain question answering is the lexicosyntactic gap between natural language questions and knowledge base entries -- there are many ways to ask a question, all with the same answer. In this paper we propose to bridge this gap by generating paraphrases of the input question with the goal that at least one of them will be correctly mapped to a knowledge-base query.

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    10. Syntagma. A Linguistic Approach to Parsing. (arXiv:1303.5960v3 [cs.CL] UPDATED)

      SYNTAGMA is a rule-based parsing system, structured on two levels: a general parsing engine and a language specific grammar. The parsing engine is a language independent program, while grammar and language specific rules and resources are given as text files, consisting in a list of constituent structuresand a lexical database with word sense related features and constraints.

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    11. Query parser derivation computing device and method for making a query parser for parsing unstructured search queries

      A system and method is provided which may comprise parsing an unstructured geographic web-search query into a field-based format, by utilizing conditional random fields, learned by semi-supervised automated learning, to parse structured information from the unstructured geographic web-search query. The system and method may also comprise establishing semi-supervised conditional random fields utilizing one of a rule-based finite state machine model and a statistics-based conditional random field model. Systematic geographic parsing may be used with the one of the rule-based finite state machine model and the statistics-based conditional random field model. Parsing an unstructured local geographical web-based query in local domain ...

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    12. Statistical Parsing by Machine Learning from a Classical Arabic Treebank. (arXiv:1510.07193v1 [cs.CL])

      Research into statistical parsing for English has enjoyed over a decade of successful results. However, adapting these models to other languages has met with difficulties. Previous comparative work has shown that Modern Arabic is one of the most difficult languages to parse due to rich morphology and free word order. Classical Arabic is the ancient form of Arabic, and is understudied in computational linguistics, relative to its worldwide reach as the language of the Quran.

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    13. Edge-Linear First-Order Dependency Parsing with Undirected Minimum Spanning Tree Inference. (arXiv:1510.07482v1 [cs.CL])

      The run time complexity of state-of-the-art inference algorithms in graph-based dependency parsing is super-linear in the number of input words (n). Recently, pruning algorithms for these models have shown to cut a large portion of the graph edges, with minimal damage to the resulting parse trees. Solving the inference problem in run time complexity determined solely by the number of edges (m) is hence of obvious importance.

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    14. System and method for dialog modeling

      Disclosed herein are systems, computer-implemented methods, and computer-readable media for dialog modeling. The method includes receiving spoken dialogs annotated to indicate dialog acts and task/subtask information, parsing the spoken dialogs with a hierarchical, parse-based dialog model which operates incrementally from left to right and which only analyzes a preceding dialog context to generate parsed spoken dialogs, and constructing a functional task structure of the parsed spoken dialogs. The method can further either interpret user utterances with the functional task structure of the parsed spoken dialogs or plan system responses to user utterances with the functional task structure of the ...

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    15. Multi-source transfer of delexicalized dependency parsers

      A source language sentence is tagged with non-lexical tags, such as part-of-speech tags and is parsed using a lexicalized parser trained in the source language. A target language sentence that is a translation of the source language sentence is tagged with non-lexical labels (e.g., part-of speech tags) and is parsed using a delexicalized parser that has been trained in the source language to produce k-best parses. The best parse is selected based on the parse's alignment with lexicalized parse of the source language sentence. The selected best parse can be used to update the parameter vector of a ...

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    16. Efficient parsing with structured prediction cascades

      A dependency parsing method can include determining an index set of possible head-modifier dependencies for a sentence. The index set can include inner arcs and outer arcs, inners arcs representing possible dependency between words in the sentence separated by a distance less than or equal to a threshold and outer arcs representing possible dependency between words in the sentence separated by a distance greater than the threshold. The index set can be pruned to include: (i) each specific inner arc when a likelihood that the specific inner arc is appropriate is greater than a first threshold, and (ii) the outer ...

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    17. Method and apparatus for full natural language parsing

      The method and apparatus for discriminative natural language parsing, uses a deep convolutional neural network adapted for text and a structured tag inference in a graph. In the method and apparatus, a trained recursive convolutional graph transformer network, formed by the deep convolutional neural network and the graph, predicts "levels" of a parse tree based on predictions of previous levels.

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    18. Method and system for generating a parser and parsing complex data

      Computer-implemented systems and methods are disclosed for constructing a parser that parses complex data. In some embodiments, a method is provided for receiving a parser definition as an input to a parser generator and generating a parser at least in part from the parser definition. In some embodiments, the generated parser comprises two or more handlers forming a processing pipeline. In some embodiments, the parser receives as input a first string into the processing pipeline. In some embodiments, the parser generates a second string by a first handler and inputs the second string regeneratively into the parsing pipeline, if the ...

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    19. Immutable parsing

      Immutable structures are employed to effect immutable parsing. In particular, an immutable parsing configuration, comprising a stack and lookahead buffer, is utilized by a parser to perform lexical and syntactical analysis of an input stream and optionally output an immutable parse tree or the like. Performance with respect to the immutable structures can be optimized utilizing sharing and lazy computation. In turn, immutability benefits are afforded with respect to parsing including safe sharing amongst services and/or across multiple threads as well as history preservation, among other things.

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    20. Methods and apparatus for dynamic embedded object handling

      A navigation information distribution system comprising one or more servers in communication with each other to parse embedded data attached to an electronic mail message. The servers are configured to receive an email including destination data associated with subscriber identification. Before parsing the embedded data, the server may confirm the subscriber identification included in the email is a valid active subscriber. After confirmation of the subscriber's status, the servers parse the destination data from the email and determine a location based on the destination data using a map database. After parsing, the server may receive a request for the ...

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    49-72 of 598 « 1 2 3 4 5 6 ... 23 24 25 »
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