P A T T R :  P A T E N T  T R A N S L A T I O N  R E S O U R C E

Download link: 	http://www.cl.uni-heidelberg.de/statnlpgroup/pattr/
Author: 	Katharina Wäschle (waeschle@cl.uni-heidelberg.de)
Date: 		28/02/2013

PatTR is a parallel corpus extracted from documents in the MAREC patent
collection [1]. The first release contains 23 million German-English
parallel sentences collected from all patent text sections.


0. TERMS OF USE

 PatTR is licensed under a Creative Commons Attribution-NonCommercial-
 ShareAlike 3.0 Unported License (see LICENSE). Please cite
 Wäschle & Riezler (2012b), if you use the corpus in your work.

1. FILES

	abstract/
		pattr.de-en.abstract.de
		pattr.de-en.abstract.en
		pattr.de-en.abstract.meta

	claims/
		pattr.de-en.claims.de
		pattr.de-en.claims.en
		pattr.de-en.claims.meta

	description/
		pattr.de-en.description.de
		pattr.de-en.description.de.meta
		pattr.de-en.description.en
		pattr.de-en.description.en.meta

	title/
		pattr.de-en.title.de
		pattr.de-en.title.en
		pattr.de-en.title.meta

 *.de files contain German sentences, *.en files corresponding English
 sentences. *.meta contain information about the document the 
 sentences were extracted from as tab-separated values:

	- document id
	- patent family id
	- publication data
	- IPC up to subclass level, comma-separated

 For the description data, where the bitext has been collected from two
 separate documents, there is a metadata file for each of the source
 documents (*.de.meta for the German document from the EPO corpus,
 *.en.meta for the English document from the USPTO corpus).

2. DATA

 The corpus is split into files according to the text sections of a
 patent document: title, abstract, claims and description.
 Parallel data from the title, abstract and claims sections were
 extracted from documents belonging to the European Patent Office
 (EPO) [2] and the World Intellectual Property Organization (WIPO) [3]
 corpora in MAREC. Both resources feature multilingual documents that
 contain for example both an English and a German abstract.

 Since there are no multilingual descriptions, data from this section
 were collected by exploiting patent families to align German documents
 from the EPO corpus to English documents from the United States Patent
 and Trademark Office (USPTO) [4] corpus, following Utiyama and Isahara
 (2007).

 All sections were sentence-aligned using the Gargantua aligner [5].
 Preprocessing was done automatically. Sentence boundaries were detected
 using the Europarl processing tools [6].

4. STATISTICS

 Section     Sentences  EN tokens     DE tokens

 title        2,101,107    16,457,527  13,212,645
 abstract       720,571    30,942,571  26,803,868
 claims       8,346,863   501,373,533 435,117,827
 description 11,829,816   498,948,414 386,920,744
 total       22,998,357 1,047,722,045 862,055,084

5. TEST SETS

 The training and test sets used in Wäschle & Riezler (2012a) can be
 provided on request to waeschle@cl.uni-heidelberg.de. For creating
 custom training and test sets, an easy option is to split the corpus by
 document publication date. Note, that abstract and claims data contain
 a small amount (less than 1%) of duplicate and near-duplicate sentences
 due to multiple instances of the same patent document in the two
 corpora. To prevent overlap, make sure family ids of test and training
 set are disjunct. Furthermore, about 7% of the description data are
 duplicates. This is caused by the patent writing process, where whole
 paragraphs are copied verbatim from other documents, e.g. when parts of
 an invention are similar to a previously filed one. These documents do
 not share a patent id, so they cannot be easily identified. Indicators
 are mutual citations and documents filed by the same company. We did
 not remove these duplicates because they are a feature of patent
 corpora. Since patent titles are very short and general, 15% of title
 data are natural duplicates.

6. ACKNOWLEDGEMENTS

 The work was in part supported by the "Cross-language Learning-to-Rank
 for Patent Retrieval" project funded by the Deutsche
 Forschungsgemeinschaft (DFG).

PUBLICATIONS

 Wäschle, K. and Riezler, S. (2012a). Structural and Topical Dimensions
 in Multi-Task Patent Translation. Proceedings of the 13th Conference of
 the European Chapter of the Association for Computational Linguistics
 (EACL 2012), Avignon, France. 
 http://www.aclweb.org/anthology-new/E/E12/E12-1083.pdf

 Wäschle, K. and Riezler, S. (2012b). Analyzing Parallelism and Domain
 Similarities in the MAREC Patent Corpus. Multidisciplinary Information
 Retrieval, pp. 12-27.
 http://www.cl.uni-heidelberg.de/~riezler/publications/papers/IRF2012.pdf

LINKS
     1. http://www.ir-facility.org/prototypes/marec
     2. http://www.epo.org
     3. http://www.wipo.int
     4. http://www.uspto.gov
     5. http://sourceforge.net/projects/gargantua
     6. http://www.statmt.org/europarl