PPDB: The Paraphrase Database

What it is about

The paper releases PPDB 1.0, a large collection of ranked paraphrases extracted from bilingual parallel corpora by pivoting (the method of Bannard and Callison-Burch). Pairs of English phrases that translate the same foreign phrase are taken as paraphrases. The English part holds over 220 million pairs: about 73 million phrasal and 8 million lexical paraphrases, and 140 million syntactic paraphrase patterns, extracted from more than 100 million sentence pairs. Each pair carries translation probabilities and distributional scores from the Google n-grams and Annotated Gigaword. The scores are combined by a fixed heuristic, and the pairs are cut into size tiers from S to XXXL, so that users can trade precision for recall. The release also includes filters for high-precision subsets and tools to extract paraphrases for other languages. The paper gives no new human evaluation; the ranking is evaluated in PPDB 2.0.

Ideas

• I1. Pivot counting for the translator's lexicon: for each English chunk that the Hebrew source aligns to, count the English words aligned to the same source chunk, and rank the merges by the product of the two conditional counts. This gives a count-based ranking of candidate concept merges, which the residual then judges (open problem 2).
• I2. Release the lexicon in tiers by score, as this paper does. The translator can then measure the reader and encoder bits at each tier and keep the largest tier where the residual still falls.
• I3. Treat recurring verse phrases with slots as construction entries in the standard encoder, counted from aligned verses. This addresses phrases that carry function words, such as unto thou, which the translator currently merges as lexical items.

For Mova

The lexicon of tools/translate/meta.rs is the place for the pivot count, and the alignments of hebrew.rs and ibm.rs are the pivot. Tiers are a plain threshold rule with a measure, which fits the rule that a gain is claimed only after a run is repeated. The licence is non-commercial, so the paper and data are read for summary only; nothing from the release is built.

Topics: Machine translation

Cite

The paper itself, not this card. BibTeX from the library's record of the work.

@inproceedings{ganitkevitch2013ppdb,
  title = {{PPDB: The Paraphrase Database}},
  author = {Ganitkevitch, Juri and Durme, Benjamin Van and Callison-Burch, Chris},
  booktitle = {Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
  year = {2013},
  url = {https://aclanthology.org/N13-1092/}
}

References

36 references, 5 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Alfred V. Aho and Jeffrey D. Ullman. 1972. The Theory of Parsing, Translation, and Compiling. Prentice Hall. find
2. Colin Bannard and Chris Callison-Burch. 2005. Paraphrasing with bilingual parallel corpora. In Proceedings of ACL. find our card
3. Jonathan Berant, Jacob Goldberger, and Ido Dagan. 2011. Global learning of typed entailment rules. In Proceedings of ACL. find
4. Rahul Bhagat and Deepak Ravichandran. 2008. Large scale acquisition of paraphrases for learning surface patterns. In Proceedings of ACL/HLT. find
5. Thorsten Brants and Alex Franz. 2006. Web 1T 5-gram version 1. ↗
6. Thorsten Brants and Alex Franz. 2009. Web 1T 5-gram, 10 european languages version 1. Linguistic Data Consortium, Philadelphia. ↗
7. Chris Callison-Burch, Philipp Koehn, Christof Monz, and Josh Schroeder. 2009. Findings of the 2009 Workshop on Statistical Machine Translation. In Proceedings of WMT, pages 1–28, Athens, Greece, March. find
8. Tsz Ping Chan, Chris Callison-Burch, and Benjamin Van Durme. 2011. Reranking bilingually extracted paraphrases using monolingual distributional similarity. In EMNLP Workshop on GEMS. find
9. David Chiang. 2005. A hierarchical phrase-based model for statistical machine translation. In Proceedings of ACL. find our card
10. Kenneth Church and Patrick Hanks. 1991. Word association norms, mutual information and lexicography. Computational Linguistics, 6(1):22–29. ↗
11. Trevor Cohn and Mirella Lapata. 2008. Sentence compression beyond word deletion. In Proceedings of the COLING. find
12. Bill Dolan, Chris Quirk, and Chris Brockett. 2004. Unsupervised construction of large paraphrase corpora: Exploiting massively parallel news sources. In Proceedings of the COLING. find
13. Andreas Eisele and Yu Chen. 2010. MultiUN: A multilingual corpus from united nation documents. In Proceedings of LREC, Valletta, Malta. find
14. Juri Ganitkevitch, Chris Callison-Burch, Courtney Napoles, and Benjamin Van Durme. 2011. Learning sentential paraphrases from bilingual parallel corpora for text-to-text generation. In Proceedings of EMNLP. find
15. Juri Ganitkevitch, Benjamin Van Durme, and Chris Callison-Burch. 2012. Monolingual distributional similarity for text-to-text generation. In Proceedings of *SEM. Association for Computational Linguistics. find
16. Paul Kingsbury and Martha Palmer. 2002. From treebank to propbank. In Proceedings of LREC. find our card
17. Philipp Koehn and Josh Schroeder. 2007. Experiments in domain adaptation for statistical machine translation. In Proceedings of WMT, Prague, Czech Republic, June. Association for Computational Linguistics. find
18. Philipp Koehn. 2005. Europarl: A parallel corpus for statistical machine translation. In MT summit, volume 5. find
19. Philipp Koehn. 2010. Statistical Machine Translation. Cambridge University Press. ↗
20. Mirella Lapata and Frank Keller. 2005. Web-based models for natural language processing. ACM Transactions on Speech and Language Processing, 2(1). ↗
21. Dekang Lin and Patrick Pantel. 2001. Discovery of inference rules from text. Natural Language Engineering. find
22. Dekang Lin, Kenneth Church, Heng Ji, Satoshi Sekine, David Yarowsky, Shane Bergsma, Kailash Patil, Emily Pitler, Rachel Lathbury, Vikram Rao, Kapil Dalwani, and Sushant Narsale. 2010. New tools for web-scale n-grams. In Proceedings of LREC. find
23. Mitchell P. Marcus, Mary Ann Marcinkiewicz, and Beatrice Santorini. 1993. Building a large annotated corpus of english: the Penn Treebank. Computational Linguistics, 19(2). ↗ our card
24. Angelo Mendonca, David Andrew Graff, and Denise DiPersio. 2009. Spanish Gigaword Second Edition. Linguistic Data Consortium. ↗
25. Ndapandula Nakashole, Gerhard Weikum, and Fabian Suchanek. 2012. PATTY: a taxonomy of relational patterns with semantic types. In Proceedings of EMNLP. find
26. Courtney Napoles, Matt Gormley, and Benjamin Van Durme. 2012. Annotated gigaword. In Proceedings of AKBC-WEKEX 2012. find
27. Roberto Navigli and Simone Paolo Ponzetto. 2012. BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artificial Intelligence, 193. find
28. Chris Quirk, Chris Brockett, and William Dolan. 2004. Monolingual machine translation for paraphrase generation. In Proceedings of EMNLP. find our card
29. Stefan Riezler, Alexander Vasserman, Ioannis Tsochantaridis, Vibhu Mittal, and Yi Liu. 2007. Statistical machine translation for query expansion in answer retrieval. In Proceedings of the 45th Annual Meeting of the ACL. find
30. Matthew Snover, Nitin Madnani, Bonnie Dorr, and Richard Schwartz. 2010. Ter-plus: paraphrase, semantic, and alignment enhancements to translation edit rate. Machine Translation, 23(2-3):117–127. ↗
31. Rion Snow, Daniel Jurafsky, and Andrew Y. Ng. 2006. Semantic taxonomy induction from heterogenous evidence. In Proceedings of the ACL/Coling. find
32. Ralf Steinberger, Bruno Pouliquen, Anna Widiger, Camelia Ignat, Tomaz Erjavec, Dan Tufis, and Dániel Varga. 2006. The JRC-Acquis: A multilingual aligned parallel corpus with 20+ languages. In Proceedings of LREC, Genoa, Italy. find
33. Jörg Tiedemann. 2009. News from OPUS: A collection of multilingual parallel corpora with tools and interfaces. In Recent Advances in Natural Language Processing, volume 5. ↗
34. Benjamin Van Durme and Ashwin Lall. 2010. Online generation of locality sensitive hash signatures. In Proceedings of ACL, Short Papers. find
35. Shiqi Zhao, Cheng Niu, Ming Zhou, Ting Liu, and Sheng Li. 2008. Combining multiple resources to improve SMT-based paraphrasing model. In Proceedings of ACL/HLT. find
36. Liang Zhou, Chin-Yew Lin, Dragos Stefan Munteanu, and Eduard Hovy. 2006. Paraeval: Using paraphrases to evaluate summaries automatically. In Proceedings of HLT/NAACL. find

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