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This paper present a new method for parsing English sentences. The parser called LUTE-EJ parser is combined with case analysis and ATNG-based analysis. LUTE-EJ parser has two interesting mechanical characteristics. …...

The paper begins by defining a class of distributed memory machines which have useful properties as retrieval and filtering devices. These memory mechanisms store large numbers of associations on a …...

This paper surveys some issues that arise in the study of the syntax and semantics of natural languages (NL's) and have potential relevance to the automatic recognition, parsing, and translation …...

The paper presents the general design and the first results of a research project whose long term goal is to develop and implement ALICE, an experimental system capable of augmenting …...

This report outlines a machine translation system whose linguistic component is based on principles of Government and Binding. A "universal grammar" is defined, together with pal-ameters of variation for specific …...

In virtually all current natural-language dialog systems, users can only refer to objects by using linguistic descriptions. How- ever, in human face-to-face conversation, participants fre= quently use various sorts of …...

We describe the modification of a grammar to take ad- vantage of prosodic information automatically extracted from speech. The work includes (1) the development of an integer "break index" representation …...

AbstractThis presentation outlines the implementation of a machine translation system for avalanche warning bulletins in natural language, using a unification-based formalism developed at ISSCO, which will be introduced at the …...

Ordinarily, one thinks of the problem of natural language un- derstanding as one of making a single, left-to-right pass through an input, producing a progressively refined and detailed interpre- tation. …...

Parsing a long sentence is very difficult, since long sentences often have conjunctions which result in am- biguities. If the conjunctive structures existing in a long sentence can be analyzed …...

It is well known that even extremely limited center- embedding causes people to have difficulty ill comprehen- sion, but that left- and right-branching constractions pro- duce no such effect. If …...

Most of tile research on parsing natnral [allguages has beetl concerned with I",nglish, or wil, h other languages nlOrl)hologically similar Io English. Parsing agglntinat.ive word st, ructures ha.s altracted relatively …...

Prosody can be useful in resolving certain lex- ical and structural ambiguities in spoken English. In this paper we present some results of employ- ing two types of prosodic information, …...

Active constraints of tile CO,lslratnl higic program- in,rig paradigm allow (l) the reduction of the search space of progr~tms and (2) a very concise representation of the problcnls. These two …...

AbstractThe Cambridge Language Survey is a research project whose activities centre around the use of an Integrated Language Database, whereby a computerised dictionary is used for intelligent cross-reference during corpus …...

We present an integrated approach to speech and natural language processing which uses a single parser to create training for a statistical speech recognition component and for interpreting recognized text. …...

This paper presents a unified approach to parsing, in which top-down, bottom- up and left-corner parsers m:e related to preorder, postorder and inorder tree traversals. It is shown that the …...

This paper describes our work on parsing Turk- ish using the lexical-functional grammar formalism. This work represents the first effort for parsing Turkish. Our implementation is based on Tomita's parser …...

We present a new apl)roach , ilhlstrated by two algo- rithms> for parsing not only Finite SI.ate (:Iranlnlars but also Context Free Grainlnars and their extension, by means of finite …...

Recent, work in ca.t;eg(Mj gr;mmt;~r has seen proposals for a wide. r;Lltg(~ O[ sys-. t;(;i[IS, differing in their 'resomx:e sensi- tivil;y' and hence, implicitly, {;heir under.. lying nol;ion of qinguisl;ie …...

We present a natural language interface system which is based entirely on trained statistical models. The system consists of three stages of processing: parsing, semantic interpretation, and discourse. Each of …...

We present a knowledge and context-based system for parsing and translating natu- ral language and evaluate it on sentences from the Wall Street Journal. Applying machine learning techniques, the system …...

Any large language processing software relies in its operation on heuristic decisions concerning the strategy of processing. These decisions are usually "hard-wired" into the software in the form of hand- …...

The lexical acquisition system presented in this pa- per increlnenlally updates linguistic properties of un- known words inferred lrom their surrounding con- lexI by parsing senlences wilh an liPSG gramnmr …...

This paper presents a technique to deal with multiword nominal terminology in a compu- tational Lexical Functional Grammar. This method treats multiword terms as single to- kens by modifying the …...

This paper presents a technique to deal with multiword nominal terminology in a compu- tational Lexical Functional Grammar. This method treats multiword terms as single to- kens by modifying the …...

In this article, we apply to natural language parsing and tagging the device of trigger- pair predictors, previously employed exclu- sively within the field of language mod- elling for speech …...

This paper proposes a method for packing fea- ture structures, which automatically collapses equivalent parts of lexical/phrasal feature struc- tures of HPSG into a single packed feature struc- ture. This …...

In this paper, parsing-as-deduction and constraint pro- gramming are brought together to outline a procedure for the specification of constraint-based chart parsers. Fol- lowing the proposal in Shieber et al. …...

This paper introduces new learning al- gorithms for natural language processing based on the perceptron algorithm. We show how the algorithms can be efficiently applied to exponential sized representa- tions …...

The paper presents a maximum entropy Chinese character-based parser trained on the Chinese Treebank (“CTB” hence- forth). Word-based parse trees CTB are first converted into character-in based trees, where word-level …...

Today, corpus plays an important role in development and evaluation language and speech technologies, such as part of speech tagging, parsing, word sense disambiguation, text categorization, named entity classification, information …...

ion of grammatical formalisms as methods for lexical disambiguation Guillaume Bonfante and Bruno Guillaume and Guy Perrier LORIA - UMR 7503, Campus Scientifique, B.P. 239, F-54506 Vandœuvre l`es Nancy CEDEX …...

This paper introduces a new approach to translation memories. The proposed translation technology uses linguistic analysis (morphology and parsing) to determine similarity between two source-language segments, and attempts to assemble …...

In this paper, we extend an existing parser to produce richer output annotated with function labels. We obtain state-of-the-art results both in function labelling and in parsing, by automatically relabelling …...

We present an approach to multi-device dia- logue that evaluates and selects amongst candi- date dialogue moves based on features at mul- tiple levels. Multiple sources of information can be …...

We show that the problems of parsing and sur- face realization for grammar formalisms with “context-free” derivations, coupled with Mon- tague semantics (under a certain restriction) can be reduced in …...

. We introduce an error mining technique for automatically detecting errors in re- sources that are used in parsing systems. We applied this technique to parsing results produced on several …...

For many language technology applications, such as question answering, the overall sys- tem runs several independent processors over the data (such as a named entity recognizer, a coreference system, and …...

This paper addresses two problems that commonly arise in parsing with precision- oriented, rule-based models of grammar: lack of speed and lack of robustness. First, we show how we can …...

AbstractIn this paper we describe FragmentSeeker, a tool which is capable to identify all those tree constructions which are recurring multiple times in a large Phrase Structure treebank. The tool …...

Tree-based translation models, which ex- ploit the linguistic syntax of source lan- guage, usually separate decoding into two steps: parsing and translation. Although this separation makes tree-based decoding simple and …...

A fundamental step in sentence compre- hension involves assigning semantic roles to sentence constituents. To accomplish this, the listener must parse the sentence, find constituents that are candidate argu- ments, …...

. In this paper, we present an application-driven low-cost concept of building a multi-purpose language resource for Czech which is based on currently available results of previous work by various …...

AbstractPersian with its about 100,000,000 speakers in the world belongs to the group of languages with less developed linguistically annotated resources and tools. The few existing resources and tools are …...

Semantic query sub-network is the representation of a natural language query as a graph of semantically connected words. Such sub-networks can be identified as sub-graphs in larger ontologies like DBpedia …...

AbstractLarge scale annotated corpora of child language can be of great value in assessing theoretical proposals regarding language acquisition models. For example, they can help determine whether the type and …...

This paper describes the development of a web-service tool for the automatic extraction of Multi-word expressions lexicons, which has been integrated in a distributed platform for the automatic creation of …...

AbstractRelation extraction (RE) is an important text mining task which is the basis for further complex and advanced tasks. In state-of-the-art RE approaches, syntactic information obtained through parsing plays a …...

Studies of gender balance in academic com- puter science are typically based on statistics on enrollment and graduation. Going beyond these coarse measures of gender participation, we conduct a fine-grained …...

Many parsers learn sparse class distributions over trees to model natural language. Recursive Neural Networks (RNN) use much denser representations, yet can still achieve an F-score of 92.06% for right …...

This paper presents a novel method of improving Combinatory Categorial Grammar (CCG) parsing using features generated from Dependency Grammar (DG) parses and combined using reranking. Different grammar formalisms have different …...

Conditional random fields and other graphi- cal models have achieved state of the art re- sults in a variety of tasks such as coreference, relation extraction, data integration, and pars- …...

In this paper, we propose the use of spans in addition to edges in noun compound analysis. A span is a sequence of words that can represent a noun compound. …...

In recent years, statistical parsers have reached high performance levels on well-edited texts. Domain adaptation techniques have improved parsing results on text genres differing from the journalistic data most parsers …...

Chunks and the notion of activation : a facilitation model for sentence processing We propose in this paper to integrate the notion of chunk within a global architecture for sentence …...

Online learning algorithms like the percep- tron are widely used for structured predic- tion tasks. For sequential search problems, like left-to-right tagging and parsing, beam search has been successfully combined …...

AbstractGrounded language learning, the task of mapping from natural language to a representation of meaning, has attracted more and more interest in recent years. In most work on this topic, …...

. We propose two discriminative strategies to integrate compound word recognition in a parsing context: (i) compound pregrouping with Conditional Random Fields before parsing, (ii) reranking parses with a maximum …...

We introduce a provably correct learning algorithm for latent-variable PCFGs. The algorithm relies on two steps: first, the use of a matrix-decomposition algorithm ap- plied to a co-occurrence matrix estimated …...

Structured perceptron becomes popular for various NLP tasks such as tagging and parsing. Practical studies on NLP did not pay much attention to its regularization. In this paper, we study …...

AbstractRevisiting the now de facto standard Stanford dependency representation, we propose an improved taxonomy to capture grammatical relations across languages, including morphologically rich ones. We suggest a two-layered taxonomy: a …...

Despite the convexity of structured max- margin objectives (Taskar et al., 2004; Tsochantaridis et al., 2004), the many ways to optimize them are not equally ef- fective in practice. We …...

Word embeddings have been found useful for many NLP tasks, including part-of-speech tagging, named entity recognition, and pars- ing. Adding multilingual context when learn- ing embeddings can improve their quality, …...

AbstractTANL is a suite of tools for text analytics based on the software architecture paradigm of data driven pipelines. The strategies for upgrading TANL to the use of Universal Dependencies …...

Parsing for a wide variety of grammar for- malisms can be performed by intersecting finite tree automata. However, naive im- plementations of parsing by intersection are very inefficient. We present …...

AbstractLight verb constructions (LVC) in Hindi are highly productive. If we can distinguish a case such as nirnay lenaa ‘decision take; decide’ from an ordinary verb-argument combination kaagaz lenaa ‘paper …...

We introduce recurrent neural network gram- mars, probabilistic models of sentences with explicit phrase structure. We explain efficient inference procedures that allow application to both parsing and language modeling. Experi- …...

Sequence-to-Sequence (seq2seq) modeling has rapidly become an important general- purpose NLP tool that has proven effective for many text-generation and sequence-labeling tasks. Seq2seq builds on deep neural language modeling and …...

In this paper we present new state-of-the-art performance on CCG supertagging and pars- ing. Our model outperforms existing ap- proaches by an absolute gain of 1.5%. We an- alyze the …...

AbstractTransfer and multi-task learning have traditionally focused on either a single source-target pair or very few, similar tasks. Ideally, the linguistic levels of morphology, syntax and semantics would benefit each …...

AbstractWe consider the problem of parsing natural language descriptions into source code written in a general-purpose programming language like Python. Existing data-driven methods treat this problem as a language generation …...

AbstractPruning hypotheses during dynamic programming is commonly used to speed up inference in settings such as parsing. Unlike prior work, we train a pruning policy under an objective that measures …...

AbstractDomain similarity measures can be used to gauge adaptability and select suitable data for transfer learning, but existing approaches define ad hoc measures that are deemed suitable for respective tasks. …...

AbstractParsing Chinese critically depends on correct word segmentation for the parser since incorrect segmentation inevitably causes incorrect parses. We investigate a pipeline approach to segmentation and parsing using word lattices …...

AbstractIn this report we summarize the results of the 2017 AMR SemEval shared task. The task consisted of two separate yet related subtasks. In the parsing subtask, participants were asked …...

AbstractWe present a graph-based Tree Adjoining Grammar (TAG) parser that uses BiLSTMs, highway connections, and character-level CNNs. Our best end-to-end parser, which jointly performs supertagging, POS tagging, and parsing, outperforms …...

AbstractPre-trained text encoders have rapidly advanced the state of the art on many NLP tasks. We focus on one such model, BERT, and aim to quantify where linguistic information is …...

AbstractRecurrent neural network grammars generate sentences using phrase-structure syntax and perform very well on both parsing and language modeling. To explore whether generative dependency models are similarly effective, we propose …...

AbstractWe use parsing as sequence labeling as a common framework to learn across constituency and dependency syntactic abstractions. To do so, we cast the problem as multitask learning (MTL). First, …...

AbstractWe use the multilingual OSCAR corpus, extracted from Common Crawl via language classification, filtering and cleaning, to train monolingual contextualized word embeddings (ELMo) for five mid-resource languages. We then compare …...

AbstractNegation is a universal linguistic phenomenon with a great qualitative impact on natural language processing applications. The availability of corpora annotated with negation is essential to training negation processing systems. …...

AbstractIn recent years, parsing performance is dramatically improved on in-domain texts thanks to the rapid progress of deep neural network models. The major challenge for current parsing research is to …...

AbstractPerformance in cross-lingual NLP tasks is impacted by the (dis)similarity of languages at hand: e.g., previous work has suggested there is a connection between the expected success of bilingual lexicon …...

AbstractAlthough parsing to Abstract Meaning Representation (AMR) has become very popular and AMR has been shown effective on the many sentence-level downstream tasks, little work has studied how to generate …...

AbstractSteedman (2020) proposes as a formal universal of natural language grammar that grammatical permutations of the kind that have given rise to transformational rules are limited to a class known …...

AbstractPretraining-based neural network models have demonstrated state-of-the-art (SOTA) performances on natural language processing (NLP) tasks. The most frequently used sentence representation for neural-based NLP methods is a sequence of subwords …...

AbstractAbstract Meaning Representation is a sentence-level meaning representation, which abstracts the meaning of sentences into a rooted acyclic directed graph. With the continuous expansion of Chinese AMR corpus, more and …...

AbstractThe traditional evaluation of labeled spans with precision, recall, and F1-score has undesirable effects due to double penalties. Annotations with incorrect label or boundaries count as two errors instead of …...

AbstractThis paper considers the task of parsing low-resource languages in a scenario where parallel English data and also a limited seed of annotated sentences in the target language are available, …...

AbstractThis paper presents the phonological, morphological, and syntactic distinctions between formal and informal Persian, showing that these two variants have fundamental differences that cannot be attributed solely to pronunciation discrepancies. …...

AbstractName Entity Recognition (NER) is a very important and basic task in traditional NLP tasks. In the biomedical field, NER tasks have been widely used in various products developed by …...

AbstractWe propose a method for formulating CCG as a recursive composition in a continuous vector space. Recent CCG supertagging and parsing models generally demonstrate high performance, yet rely on black-box …...