The MULTINOT project aims at the creation of a parallel English-Spanish corpus which is balanced –in terms of register diversity and translation directions– and whose design and enrichment with multidimensional annotations focuses on quality rather than on quantity.

The project offers the scientific community a multifunctional resource which can be used by a variety of potential users and in a number of theoretical and applied contexts, such as, e.g.: 

- linguists working on contrastive and corpus-based analysis

- translators in need of bilingual parallel texts in both directions

- translation trainers as a resource for computer-assisted translation

- language teachers and computational linguists developing NLP applications.

The resulting corpus –the MULTINOT corpus– is a one-million-word sentence-aligned, and multidimensionally-annotated parallel corpus for the language pair English-Spanish.

            The MULTINOT corpus distinguishes itself from other parallel corpora by having a balanced composition (both in terms of registers and translation directions) and by focusing on quality rather than quantity. Thus, during the data collection phase, we made sure that the text samples were extracted from published online materials provided by publishing houses, press, government, corporate enterprises, European institutions, and other organisations under the ‘fair use’ agreement. Also, during data processing we also focused on corpus quality by manually correcting text samples at different processing stages such as sentence splitting, alignment and part-of-speech tagging. Furthermore, interannotator agreement has been carried out for the manual annotation phase of several higher level features, such as MODALITY, THEMATISATION, RHETORICAL STRUCTURES and PROJECTION.

 The corpus currently contains the proportions of texts specified in table 1: 

MacroRegister	Sub-register	Source=> Target	English	Spanish	Total
Literature	Novels	EN=>ES	24886 orig	26927 trans	51813
		ES=>EN	27939 tran	26672 orig	54611
	Short stories	EN=>ES	2186 orig	2088 trans	4274
		ES=>EN	1175 orig	1197 trans	2372
	Essays	EN=>ES	27382 orig	27235 trans	54617
		ES=>EN	32517 trans	30362 orig	62879
Journalism	News reporting articles (popsci)	EN=>ES	10658 orig	9753 trans	20411
		ES=>EN	24579 orig	23730 trans	48309
Administrative	Official speeches	EN=>ES	25373 orig	27112 trans	52485
		ES=>EN
	Proceedings of debates	EN=>ES	25620 orig	26450 trans	52070
		ES=>EN	27390 orig	26320 trans	53710
External communication	Promotion/advertising brochures	EN=>ES	23695 orig	27790 trans	51485
		ES=>EN	25761 orig	25367 trans	51128
	Self-presentation documents	EN=>ES
		ES=>EN	31188 orig	27326 trans	58514
	Scientific texts	EN=>ES	42580 orig	45047 trans	87627
		ES=>EN	24322 orig	23430 trans	47742
	Legal procedures	EN=>ES	36688 orig	38640 trans	75328
		ES=>EN	23984 orig	22185 trans	46169

 Table 1: Word count distribution of different registers in MULTINOT (June 2015)

 

All documents are normalized, preprocessed through the LeTs preprocessing pipeline (Van de Kauter et al. 2013) and aligned. Preprocessing includes automatic and manual correction of: 

• Multiple POS tags and lemmatization
• Sentence segmentation 
• Basic Document structure in TEI XML

In addition, certain subregisters include manual annotation layers of semantic, pragmatic and discourse features, as follows:

• Modality values (epistemic, deontic, dynamic and volitional values and their subtypes)
• Thematic selection and Progression Patterns 
• Projection 
• Discourse Markers

            In order to enable corpus users to query the corpus selecting the texts that fulfill their specific needs, each sample has an accompanying metadata file including text-related and translation-related information. The whole corpus is released in XML format, and made available through a password-protected online interface to be requested from the project"s principal investigator (Dr. Julia Lavid).

Financing body: Spanish Ministry of Economy and Competitiveness (MINECO) for the period: January 2013-Dec. 2015, with an extension until 31st December 2016.

Reference: FFI2012-32201

Principal Investigator (IP): Dr. Julia Lavid López

 

MODALITY meanings and their realisations in English and Spanish

The MODALITY layer provides an analysis of the English original and translated texts, as well as of the Spanish original texts and their translations into Enlgish. The MODAL values which were used and their realisation features are graphically presented in Figure 1 below: 

Figure 1: Screenshot of Modality Layer in MULTINOT

  

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