Morphological Disambiguation by Voting Constraints

We present a constraint-based morphological disambiguation system in which individual constraints vote on matching morphological parses, and disambiguation of all the tokens in a sentence is performed at the end by selecting parses that receive the highest votes. This constraint application paradigm makes the outcome of the disambiguation independent of the rule sequence, and hence relieves the rule developer from worrying about potentially conflicting rule sequencing. Our results for disambiguating Turkish indicate that using about 500 constraint rules and some additional simple statistics, we can attain a recall of 95-96% and a precision of 94-95% with about 1.01 parses per token. Our system is implemented in Prolog and we are currently investigating an efficient implementation based on finite state transducers.Comment: 8 pages, Latex source. To appear in Proceedings of ACL/EACL'97 Compressed postscript also available as ftp://ftp.cs.bilkent.edu.tr/pub/ko/acl97.ps.

Dependency parsing with an extended finite-state approach

This article presents a dependency parsing scheme using an extended finite-state approach. The parser augments input representation with "channels" so that links representing syntactic dependency relations among words can be accommodated and iterates on the input a number of times to arrive at a fixed point. Intermediate configurations violating various constraints of projective dependency representations such as no crossing links and no independent items except sentential head are filtered via finite-state filters. We have applied the parser to dependency parsing of Turkish

Tehokas sisäänpäindeterministisiin automaatteihin perustuva Constraint Grammar -jäsennin

Proceeding volume: 14 (2011)Pappret conceptualizes parsning med Constraint Grammar på ett nytt sätt som en process med två viktiga representationer. En representation innehåller lokala tvetydighet och den andra sammanfattar egenskaperna hos den lokala tvetydighet klasser. Båda representationer manipuleras med ren finite-state metoder, men deras samtrafik är en ad hoc -tillämpning av rationella potensserier. Den nya tolkningen av parsning systemet har flera praktiska fördelar, bland annat det inåt deterministiska sättet att beräkna, representera och räkna om alla potentiella tillämpningar av reglerna i meningen.Paperi uudelleenkonseptualisoi Constraint Grammarin sellaisena viitekehyksenä, jossa säännöt tarkentavat paikallisen ambiguiteetin tiivistä esitysmuotoa samalla kun sääntöjen ehdot sovitetaan piirrevektoreita vasten, jotka esittävät tiivistetyjen esitysmuotojen summia. Molemmat näkökulmat monitulkintaisuuteen käsitellään käyttäen puhtaita (pure) äärellistilaisia operaatioita. Tiivis esitysmuoto kuvataan piirrevektoreihin rationaalisten potenssisarjojen avulla. Tämä yhteys ei ole yhtään vähemmän puhdas kuin aikaisemmin vallalla ollut tulkinta, jonka edellyttää että leksikaalisen transduktorin tuottama sanan luentajoukko maagisesti linearisoidaan merkatuksi luentojen peräkkäinasetteluksi, joka syötetään puhtaille (äärellistilaisille) transduktoreille. Esitetyllä lähestymistavalla on useita käytännöllisiä etuja: mm. sisäänpäin deterministinen tapa laskea, esittää ja ylläpitää kaikki mahdolliset kohdat, joissa säännöt voivat soveltua virkkeeseen.The paper reconceptualizes Constraint Grammar as a framework where the rules refine the compact representations of local ambiguity while the rule conditions are matched against a string of feature vectors that summarize the compact representations. Both views to the ambiguity are processed with pure finite-state operations. The compact representations are mapped to feature vectors with the aid of a rational power series. This magical interconnection is not less pure than a prevalent interpretation that requires that the reading set provided by a lexical transducer is magically linearized to a marked concatenation of readings given to pure transducers. The current approach has several practical benefits, including the inward deterministic way to compute, represent and maintain all the applications of the rules in the sentence.Peer reviewe

A Finite State Constraint Grammar Parser

Proceedings of the NODALIDA 2011 Workshop Constraint Grammar Applications. Editors: Eckhard Bick, Kristin Hagen, Kaili Müürisep, Trond Trosterud. NEALT Proceedings Series, Vol. 14 (2011), 35–40. © 2011 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/19231

On Dependency Analysis via Contractions and Weighted FSTs

Arc contractions in syntactic dependency graphs can be used to decide which graphs are trees. The paper observes that these contractions can be expressed with weighted finite-state transducers (weighted FST) that operate on string-encoded trees. The observation gives rise to a finite-state parsing algorithm that computes the parse forest and extracts the best parses from it. The algorithm is customizable to functional and bilexical dependency parsing, and it can be extended to non-projective parsing via a multi-planar encoding with prior results on high recall. Our experiments support an analysis of projective parsing according to which the worst-case time complexity of the algorithm is quadratic to the sentence length, and linear to the overlapping arcs and the number of functional categories of the arcs. The results suggest several interesting directions towards efficient and highprecision dependency parsing that takes advantage of the flexibility and the demonstrated ambiguity-packing capacity of such a parser.Peer reviewe

Proceedings

Proceedings of the NODALIDA 2011 Workshop Constraint Grammar Applications. Editors: Eckhard Bick, Kristin Hagen, Kaili Müürisep, Trond Trosterud. NEALT Proceedings Series, Vol. 14 (2011), vi+69 pp. © 2011 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/19231

Semantic Parsing with Bayesian Tree Transducers

Many semantic parsing models use tree transformations to map between natural language and meaning representation. However, while tree transformations are central to several state-of-the-art approaches, little use has been made of the rich literature on tree automata. This paper makes the connection concrete with a tree transducer based semantic parsing model and suggests that other models can be interpreted in a similar framework, increasing the generality of their contributions. In particular, this paper further introduces a variational Bayesian inference algorithm that is applicable to a wide class of tree transducers, producing state-of-the-art semantic parsing results while remaining applicable to any domain employing probabilistic tree transducers.9 page(s

Learning Tree Distributions by Hidden Markov Models

Hidden tree Markov models allow learning distributions for tree structured data while being interpretable as nondeterministic automata. We provide a concise summary of the main approaches in literature, focusing in particular on the causality assumptions introduced by the choice of a specific tree visit direction. We will then sketch a novel non-parametric generalization of the bottom-up hidden tree Markov model with its interpretation as a nondeterministic tree automaton with infinite states.Comment: Accepted in LearnAut2018 worksho