Tree Adjoining Grammars Research Articles

XLIFF: Multilingual Translation Memory Management among Divergent Language Families

For the purpose of localization, only textual output is not sufficing the need of Machine Translation unless until it is in a usable format. In Indian scenario, localization as an industry has not been recognized yet which had led to lack of Language Standards leading to varied translation quality. Localization is the process of adapting a product or service to a particular language, culture, and desired local look-and-feel Machine Translation is one of the most important activities under localization but it is not complete unless until it is adapted by end user in a desired manner. In this paper, we are introducing format retention utility using XLIFF as an important tool to English to Indian Language Machine Translation. Machine translation (MT) is the technique of translating source text of input language into the target language text. This process uses bilingual data set along with other language assets to frame language and phrase models which are used while translating text in machine translation. Here, Machine Translation System (MTS) that uses the Tree Adjoining Grammar (TAG) is considered. Here, uniqueness and complexity of task has been discussed. In this paper, we are proposing a design and architecture to support the system along with experiments, results and future aspects. It is closely related to the long-term vision of enabling code to support local, regional, language, or culturally related preferences.

TRAINING TREE ADJOINING GRAMMARS WITH HUGE TEXT CORPUS USING SPARK MAP REDUCE

Tree adjoining grammars (TAGs) are mildly context sensitive formalisms used mainly in modelling natural languages. Usage and research on these psycho linguistic formalisms have been erratic in the past decade, due to its demanding construction and difficulty to parse. However, they represent promising future for formalism based NLP in multilingual scenarios. In this paper we demonstrate basic synchronous Tree adjoining grammar for English-Tamil language pair that can be used readily for machine translation. We have also developed a multithreaded chart parser that gives ambiguous deep structures and a par dependency structure known as TAG derivation. Furthermore we then focus on a model for training this TAG for each language using a large corpus of text through a map reduce frequency count model in spark and estimation of various probabilistic parameters for the grammar trees thereafter; these parameters can be used to perform statistical parsing on the trained grammar.

A syntactic component for Vietnamese language processing

This paper presents the development of a syntactic component for the Vietnamese language. We first discuss the construction of a lexicalized tree-adjoining grammar using an automatic extraction approach. We then present the construction and evaluation of a deep syntactic parser based on the extracted grammar. This is a complete system integrating necessary tools to process Vietnamese text, which permits to take as input raw texts and produce syntactic structures. A dependency annotation scheme for Vietnamese and an algorithm for extracting dependency structures from derivation trees are also proposed. At present, this is the first Vietnamese parsing system capable of producing both constituency and dependency analyses with encouraging performances: 69.33% and 73.21% for constituency and dependency analysis accuracy, respectively. The parser also compares favourably to a statistical parser which is trained and tested on the same data sets.

A Python-based Interface for Wide Coverage Lexicalized Tree-adjoining Grammars

Abstract This paper describes the design and implementation of a Python-based interface for wide coverage Lexicalized Tree-adjoining Grammars. The grammars are part of the XTAG Grammar project at the University of Pennsylvania, which were hand-written and semi-automatically curated to parse real-world corpora. We provide an interface to the wide coverage English and Korean XTAG grammars. Each XTAG grammar is lexicalized, which means at least one word selects a tree fragment (called an elementary tree or etree). Derivations for sentences are built by combining etrees using substitution (replacement of a tree node with an etree at the frontier of another etree) and adjunction (replacement of an internal tree node in an etree by another etree). Each etree is associated with a feature structure representing constraints on substitution and adjunction. Feature structures are combined using unification during the combination of etrees. We plan to integrate our toolkit for XTAG grammars into the Python-based Natural Language Toolkit (NLTK: nltk.org). We have provided an API capable of searching the lexicalized etrees for a given word or multiple words, searching for a etree by name or function, display the lexicalized etrees to the user using a graphical view, display the feature structure associated with each tree node in an etree, hide or highlight features based on a regular expression, and browsing the entire tree database for each XTAG grammar.

Multiple Adjunction in Feature-Based Tree-Adjoining Grammar

In parsing with Tree Adjoining Grammar (TAG), independent derivations have been shown by Schabes and Shieber (1994) to be essential for correctly supporting syntactic analysis, semantic interpretation, and statistical language modeling. However, the parsing algorithm they propose is not directly applicable to Feature-Based TAGs (FB-TAG). We provide a recognition algorithm for FB-TAG that supports both dependent and independent derivations. The resulting algorithm combines the benefits of independent derivations with those of Feature-Based grammars. In particular, we show that it accounts for a range of interactions between dependent vs. independent derivation on the one hand, and syntactic constraints, linear ordering, and scopal vs. nonscopal semantic dependencies on the other hand.

A statistical model for grammar mapping

AbstractThe two main classes of grammars are (a) hand-crafted grammars, which are developed by language experts, and (b) data-driven grammars, which are extracted from annotated corpora. This paper introduces a statistical method for mapping the elementary structures of a data-driven grammar onto the elementary structures of a hand-crafted grammar in order to combine their advantages. The idea is employed in the context of Lexicalized Tree-Adjoining Grammars (LTAG) and tested on two LTAGs of English: the hand-crafted LTAG developed in the XTAG project, and the data-driven LTAG, which is automatically extracted from the Penn Treebank and used by the MICA parser. We propose a statistical model for mapping any elementary tree sequence of the MICA grammar onto a proper elementary tree sequence of the XTAG grammar. The model has been tested on three subsets of the WSJ corpus that have average lengths of 10, 16, and 18 words, respectively. The experimental results show that full-parse trees with average F1-scores of 72.49, 64.80, and 62.30 points could be built from 94.97%, 96.01%, and 90.25% of the XTAG elementary tree sequences assigned to the subsets, respectively. Moreover, by reducing the amount of syntactic lexical ambiguity of sentences, the proposed model significantly improves the efficiency of parsing in the XTAG system.

Lexicalization and Generative Power in CCG

The weak equivalence of Combinatory Categorial Grammar (CCG) and Tree-Adjoining Grammar (TAG) is a central result of the literature on mildly context-sensitive grammar formalisms. However, the categorial formalism for which this equivalence has been established differs significantly from the versions of CCG that are in use today. In particular, it allows restriction of combinatory rules on a per grammar basis, whereas modern CCG assumes a universal set of rules, isolating all cross-linguistic variation in the lexicon. In this article we investigate the formal significance of this difference. Our main result is that lexicalized versions of the classical CCG formalism are strictly less powerful than TAG.

On the Effect of the IO-Substitution on the Parikh Image of Semilinear Full AFLs

Back in the 1980's, the class of mildly context-sensitive formalisms was introduced so as to capture the syntax of natural languages. While the languages generated by such formalisms are constrained by the constant-growth property, the most well-known and used ones--like tree-adjoining grammars or multiple context-free grammars--generate languages which verify the stronger property of being semilinear. In (Bourreau et al. 2012), the operation of IO-substitution was created so as to exhibit mildly-context sensitive classes of languages which are not semilinear. In the present article, we extend the notion of semilinearity, and characterize the Parikh image of the languages in IO(L), the closure of a class L of semilinear languages under IO-substitution, as universally-semilinear. Based on this result and on the work of Fischer on macro-grammars, we then show that IO(L) is not closed under inverse homomorphism when L is closed under inverse homomorphism, and encompasses the class of regular languages. This result proves that IO(MCFL) is not a full AFL, where $$\mathbf {MCFL}$$MCFL denotes the class of multiple context-free languages, closing an open question in Bourreau et al. (2012). More importantly, our proof gives an insight into the relation between the non-closure under inverse homomorphism of $$\mathbf {IO(MCFL)}$$IO(MCFL) and how IO-substitution breaks semilinearity.

Bimorphisms and synchronous grammars

We tend to think of the study of language as proceeding by characterizing the strings and structures of a language, and we think of natural language processing as using those structures to build systems of utility in manipulating the language. But many language-related problems are more fruitfully viewed as requiring the specification of a relation between two languages, rather than the specification of a single language. We provide a synthesis and extension of work that unifies two approaches to such language relations: the automata-theoretic approach based on tree transducers that transform trees to their counterparts in the relation, and the grammatical approach based on synchronous grammars that derive pairs of trees in the relation. In particular, we characterize synchronous tree-substitution grammars and synchronous tree-adjoining grammars in terms of bimorphisms, which have previously been used to characterize tree transducers. In the process, we provide new approaches to formalizing the various concepts: a metanotation for describing varieties of tree automata and transducers in equational terms; a rigorous formalization of tree-adjoining and tree-substitution grammars and their synchronous counterparts, using trees over ranked alphabets; and generalizations of tree-adjoining grammar allowing multiple adjunction.

Multidimensional trees and a Chomsky–Schützenberger–Weir representation theorem for simple context-free tree grammars

Weir [34] proved a Chomsky-Schutzenberger-like representation theorem for the string languages of tree-adjoining grammars, where the Dyck language Dn in the Chomsky-Schutzenberger characterization is replaced by the intersection D2n ∩ g(D2n), where g is a certain bijection on the alphabet consisting of 2n pairs of brackets. This paper presents a generalization of this theorem to the string languages that are the yield images of the tree languages generated by simple (i.e., linear and non-deleting) context-free tree grammars. This result is obtained through a natural generalization of the original Chomsky-Schutzenberger theorem to the tree languages of simple context-free tree grammars. We use Rogers’s [24,23] notion of multi-dimensional trees to state this latter theorem in a very general, abstract form.

Syntax-driven semantic frame composition in Lexicalized Tree Adjoining Grammars

The grammar framework presented in this paper combines Lexicalized Tree Adjoining Grammar (LTAG) with a (de)compositional frame semantics. We introduce elementary constructions as pairs of elementary LTAG trees and decompositional frames. The linking between syntax and semantics can largely be captured by such constructions since in LTAG, elementary trees represent full argument projections. Substitution and adjunction in the syntax then trigger the unification of the associated semantic frames, which are formally defined as base-labelled feature structures. Moreover, the system of elementary constructions is specified in a metagrammar by means of tree and frame descriptions. This metagrammatical factorization gives rise to a fine-grained decomposition of the semantic contributions of syntactic building blocks, and it allows us to separate lexical from constructional contributions and to carve out generalizations across constructions. In the second half of the paper, we apply the framework to the analysis of directed motion expressions and of the dative alternation in English, two well-known examples of the interaction between lexical and constructional meaning.

Incremental, Predictive Parsing with Psycholinguistically Motivated Tree-Adjoining Grammar

Psycholinguistic research shows that key properties of the human sentence processor are incrementality, connectedness (partial structures contain no unattached nodes), and prediction (upcoming syntactic structure is anticipated). There is currently no broad-coverage parsing model with these properties, however. In this article, we present the first broad-coverage probabilistic parser for PLTAG, a variant of TAG that supports all three requirements. We train our parser on a TAG-transformed version of the Penn Treebank and show that it achieves performance comparable to existing TAG parsers that are incremental but not predictive. We also use our PLTAG model to predict human reading times, demonstrating a better fit on the Dundee eye-tracking corpus than a standard surprisal model.

Prefix probabilities for linear context-free rewriting systems

We present a novel method for the computation of so-called prefix probabilities for linear context-free rewriting systems. Our technique streamlines previous procedures to compute prefix probabilities for probabilistic context-free grammars, probabilistic synchronous context-free grammars and probabilistic tree adjoining grammars. In addition, the methodology is general enough to be used for a wider range of problems involving, for example, several prefixes.

Using synchronous tree adjoining grammar to model the typology of bound variable pronouns

This article presents a novel analysis of bound variable anaphora using Synchronous Tree Adjoining Grammar (STAG), a pairing of a Tree Adjoining Grammar (TAG) for syntax and a TAG for semantics. While a bound variable pronoun can occur at a distance from its binder, as in ‘Every girli believes that shei is intelligent’, languages vary, though in a limited way, as to how near or far from its binder a bound variable should be. As any dependency between two syntactic objects must be localized to a single predicate domain in TAG, modelling bound variable anaphora in syntax and semantics poses an interesting challenge for STAG. In our analysis, bound variable pronouns are represented as Multi-Component sets in both syntax and semantics, composing in delayed tree-local derivations. This allows us to not only account for variable binding at a distance, but it also allows us to define a single derivational parameter with which observed patterns of bound variable locality can be modelled, ruling out unobserved patterns, while capturing the range of interpretive possibilities for bound variable pronouns across languages.

PreRkTAG: Prediction of RNA Knotted Structures Using Tree Adjoining Grammars

Background: RNA molecules play many important regulatory, catalytic and structural roles in the cell, and RNA secondary structure prediction with pseudoknots is one the most important problems in biology. An RNA pseudoknot is an element of the RNA sec ondary structure in which bases of a single-stranded loop pair with complementary bases outside the loop. Modeling these nested structures (pseudoknots) causes numerous com putational diffilties and so it has been generally neglected in RNA structure prediction algorithms. Objectives: In this study, we present a new heuristic algorithm for the Prediction of RNA Knotted structures using Tree Adjoining Grammars (named PreRKTAG). Materials and Methods: For a given RNA sequence, PreRKTAG uses a genetic algorithm on tree adjoining grammars to propose a structure with minimum thermodynamic energy. The genetic algorithm employs a subclass of tree adjoining grammars as individuals by which the secondary structure of RNAs are modeled. Upon the tree adjoining grammars, new crossover and mutation operations were designed.The finess function is defied ac cording to the RNA thermodynamic energy function, which causes the algorithm conver gence to be a stable structure. Results: The applicability of our algorithm is demonstrated by comparing its iresults with three well-known RNA secondary structure prediction algorithms that support crossed structures. Conclusions: We performed our comparison on a set of RNA sequences from the RNAseP database, where the outcomes show effiency and practicality of the proposed algorithm.

XMG: eXtensible MetaGrammar

In this article, we introduce eXtensible MetaGrammar (XMG), a framework for specifying tree-based grammars such as Feature-Based Lexicalized Tree-Adjoining Grammars (FB-LTAG) and Interaction Grammars (IG). We argue that XMG displays three features that facilitate both grammar writing and a fast prototyping of tree-based grammars. Firstly, XMG is fully declarative. For instance, it permits a declarative treatment of diathesis that markedly departs from the procedural lexical rules often used to specify tree-based grammars. Secondly, the XMG language has a high notational expressivity in that it supports multiple linguistic dimensions, inheritance, and a sophisticated treatment of identifiers. Thirdly, XMG is extensible in that its computational architecture facilitates the extension to other linguistic formalisms. We explain how this architecture naturally supports the design of three linguistic formalisms, namely, FB-LTAG, IG, and Multi-Component Tree-Adjoining Grammar (MC-TAG). We further show how it permits a straightforward integration of additional mechanisms such as linguistic and formal principles. To further illustrate the declarativity, notational expressivity, and extensibility of XMG, we describe the methodology used to specify an FB-LTAG for French augmented with a unification-based compositional semantics. This illustrates both how XMG facilitates the modeling of the tree fragment hierarchies required to specify tree-based grammars and of a syntax/semantics interface between semantic representations and syntactic trees. Finally, we briefly report on several grammars for French, English, and German that were implemented using XMG and compare XMG with other existing grammar specification frameworks for tree-based grammars.

Tree parsing for tree-adjoining machine translation

Tree parsing is an important problem in statistical machine translation. In this context, one is given (a) a synchronous grammar that describes the translation from one language into another and (b) a recognizable set of trees; the aim is to construct a finite representation of the set of those derivations that derive elements from the given set, either on the source side (input restriction) or on the target side (output restriction). In tree-adjoining machine translation the grammar is a kind of synchronous tree-adjoining grammar. For this case, only partial solutions to the tree parsing problem have been described, some being restricted to the unweighted case, some to the monolingual case. We introduce a class of synchronous tree-adjoining grammars which is effectively closed under input and output restrictions to weighted regular tree languages, i.e. the restricted translations can again be represented by grammars in the same class; this enables, e.g. cascading restrictions. Moreover, we present an algorithm that constructs these grammars for input and output restriction.

Wo stehen wir in der Grammatiktheorie? Bemerkungen anlässlich eines Buchs von Stefan Müller

Abstract Stefan Müller’s recent introductory textbook, “Grammatiktheorie”, is an astonishingly comprehensive and insightful survey for beginning students of the present state of syntactic theory. Müller’s inspiring exposition of modern grammatical reasoning, which takes into account frameworks as diverse as Categorial Grammar, Tree Adjoining Grammar, Head-driven Phrase Structure Grammar, Minimalism and Construction Grammar (among others!), leads us to an exploration of the validity of the popular claim that grammar theory provides explanations for the human ability to acquire and use linguistic skills. To what extent this claim is justified seems unclear in light of the recent wealth of developments in neighboring fields such as computational linguistics, corpus linguistics, psycholinguistics, and statistical language modeling. In the first section of the paper, we discuss what we perceive to be a widening gap between the claims to all-embracing explanation in theoretical linguistics and the increasingly disturbing neglect of a vast field of new data and analyses in the above-mentioned related disciplines. Section 2 gives a condensed survey of the contents of Müller’s book and discusses the relationships between the various frameworks. We conclude with sceptical remarks on the book’s preference of breadth over depth, the legacy of traditional grammar theory, and the future perspective of linguistics.

A dependency perspective on the adequacy of tree local multi-component tree adjoining grammar

A dependency perspective on the adequacy of tree local multi-component tree adjoining grammar

Tree-Adjoining Grammars Are Not Closed Under Strong Lexicalization

A lexicalized tree-adjoining grammar is a tree-adjoining grammar where each elementary tree contains some overt lexical item. Such grammars are being used to give lexical accounts of syntactic phenomena, where an elementary tree defines the domain of locality of the syntactic and semantic dependencies of its lexical items. It has been claimed in the literature that for every tree-adjoining grammar, one can construct a strongly equivalent lexicalized version. We show that such a procedure does not exist: Tree-adjoining grammars are not closed under strong lexicalization.