Corpus ID: 9895822

Semi-Markov Phrase-Based Monolingual Alignment

@inproceedings{Yao2013SemiMarkovPM,
  title={Semi-Markov Phrase-Based Monolingual Alignment},
  author={Xuchen Yao and Benjamin Van Durme and Chris Callison-Burch and P. Clark},
  booktitle={EMNLP},
  year={2013}
}
We introduce a novel discriminative model for phrase-based monolingual alignment using a semi-Markov CRF. Our model achieves stateof-the-art alignment accuracy on two phrasebased alignment datasets (RTE and paraphrase), while doing significantly better than other strong baselines in both non-identical alignment and phrase-only alignment. Additional experiments highlight the potential benefit of our alignment model to RTE, paraphrase identification and question answering, where even a naive… Expand
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References

SHOWING 1-10 OF 45 REFERENCES
A Joint Phrasal and Dependency Model for Paraphrase Alignment
TLDR
A new model for monolingual alignment is presented in which the score of an alignment decomposes over both the set ofaligned phrases as well as a set of aligned dependency arcs. Expand
A Phrase-Based Hidden Semi-Markov Approach to Machine Translation
TLDR
A latent variable phrase-based translation model inspired by the hidden semi-Markov models, that does not degrade the system and is observed that both Baum-Welch and Viterbi trainings obtain the very same result, suggesting that most of the probability mass is gathered into one single bilingual segmentation. Expand
Gappy Phrasal Alignment By Agreement
TLDR
A principled and efficient phrase-to-phrase alignment model, useful in machine translation as well as other related natural language processing problems, that shows substantial improvements in both alignment quality and translation quality over word-based Hidden Markov Models, while maintaining asymptotically equivalent runtime. Expand
A Lightweight and High Performance Monolingual Word Aligner
TLDR
A discriminatively trained monolingual word aligner that uses a Conditional Random Field to globally decode the best alignment with features drawn from source and target sentences to give state-of-the-art result. Expand
Optimal and Syntactically-Informed Decoding for Monolingual Phrase-Based Alignment
TLDR
This work examines a state-of-the-art structured prediction model for the alignment task which uses a phrase-based representation and is forced to decode alignments using an approximate search approach and proposes a straightforward exact decoding technique based on integer linear programming that yields order- of-magnitude improvements in decoding speed. Expand
Learning to Paraphrase: An Unsupervised Approach Using Multiple-Sequence Alignment
TLDR
This work applies multiple-sequence alignment to sentences gathered from unannotated comparable corpora: it learns a set of paraphrasing patterns represented by word lattice pairs and automatically determines how to apply these patterns to rewrite new sentences. Expand
A Phrase-Based Alignment Model for Natural Language Inference
TLDR
The MANLI system is presented, a new NLI aligner designed to address the alignment problem, which uses a phrase-based alignment representation, exploits external lexical resources, and capitalizes on a new set of supervised training data. Expand
Discriminative Word Alignment with Conditional Random Fields
TLDR
A novel approach for inducing word alignments from sentence aligned data using a Conditional Random Field, a discriminative model, which is estimated on a small supervised training set, and which has efficient training and decoding processes which both find globally optimal solutions. Expand
Aligning Predicates across Monolingual Comparable Texts using Graph-based Clustering
TLDR
This work constructs a large corpus resource of comparable texts, including an evaluation set with manual predicate alignments, and presents a novel approach for aligning predicates across comparable texts using graph-based clustering with Mincuts. Expand
What is the Jeopardy Model? A Quasi-Synchronous Grammar for QA
TLDR
A probabilistic quasi-synchronous grammar, inspired by one proposed for machine translation, and parameterized by mixtures of a robust nonlexical syntax/alignment model with a(n optional) lexical-semantics-driven log-linear model is proposed. Expand
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