English-Tamil Political Domain Parallel Corpora

A high-quality bilingual dataset containing sentence-aligned English-Tamil text pairs for the Political domain. Supports translation, NLP, and LLM training.

About This OTS Dataset

Introduction

The English-Tamil Political Parallel Corpus is a specialized bilingual dataset curated to support the development of political-domain machine translation systems, large language models, and NLP tools. With more than 50,000 high-quality sentence pairs, it captures the language, nuance, and structure of political communication across English and Tamil, making it ideal for a wide range of cross-lingual political AI applications.

Dataset Content

•Volume and Linguistic Diversity

•Total Sentences: 50,000+ English-Tamil sentence pairs

•Translator Pool: 200+ native Tamil linguists with domain familiarity

•Language Style: Varied tone and register, covering both formal and informal political discourse

•Sentence Structure and Variety

•Word Range: Sentences span from 7 to 25 words

•Grammatical Diversity: Includes simple, compound, and complex constructions

•Sentence Forms: Features declarative, interrogative, imperative, affirmative, and negative statements

•Voice Variation: Balanced distribution of active and passive voice

•Bidirectional Structure: Portions of the dataset are translated both from English to Tamil and vice versa to strengthen multilingual alignment in both directions

•Stylistic Elements:

•Figurative language and idiomatic expressions

•Logical connectors and discourse markers

•Questions and rhetorical forms used in debates and public discourse

Domain-Specific Coverage

•Political Lexicon and Terminology

The corpus includes specialized vocabulary from subdomains such as:

•Governance and policy

•Elections and political parties

•Lawmaking and legislation

•Public opinion and political ideologies

•Geopolitics and diplomacy

•Contextual Scenarios

Sentences are contextually rooted in a variety of real-world political formats, including:

•Political speeches and debates

•Legislative drafts and policy briefs

•News reports and editorials

•Public statements and diplomatic notes

•Social media posts and civic engagement content

•Cross-Domain Relevance

To reflect the multidimensional nature of political language, the dataset also covers:

•International relations

•Human rights and social justice

•Economics and public policy

•Activism and civil society

Format and Structure

•

Available File Types: Delivered in Excel format with optional conversions to JSON, TMX, XLIFF, XML, and other formats

•Fields Included:

•Serial Number

•Unique ID

•Source Sentence + Word Count

•Target Sentence + Word Count

Usage and Applications

•

Political Machine Translation: Localize political content for government portals, international diplomacy, and media coverage

•

Multilingual NLP Applications: Build political sentiment analyzers, automated fact-checkers, and summarization tools

•

LLM Training: Fine-tune large language models for political domain understanding, question answering, and policy generation

•

Content Moderation: Use for training models that detect political bias, misinformation, or policy stance

Alignment Confidence and Quality Assurance

•

Manual Review: Every sentence pair has been manually reviewed and validated for alignment accuracy and semantic consistency

•

Linguistic Precision: Domain-specific tone, word choice, and cultural context are carefully preserved

•

Consistency Audits: Formality levels, punctuation, and terminology are standardized across batches

Tokenization and Preprocessing

•

Raw or Processed Delivery: Dataset can be delivered in raw format or with preprocessing

•Preprocessing Options (upon request):

•Tokenization

•POS tagging

•Sentence-type classification (e.g., declarative, interrogative)

•Named Entity Recognition (NER)

•Political stance or intent labeling

•Subdomain tagging (e.g., electoral politics, international policy)

Secure and Ethical Collection

•

Collection Platform: Created entirely through FutureBeeAI’s proprietary and secure platform, Yugo

•

Data Privacy: No personally identifiable information (PII) included

•

Security Protocol: All data was created and stored in-house with strict access control

•

IP Compliance: All content is original and rights-cleared, designed specifically for dataset usage

Updates and Customization

To ensure long-term value and adaptability:

•

Periodic Updates: New sentence pairs, evolving terminology, and emerging political themes are regularly added

•Customization Options:

•Domain-specific corpora in other languages or dialects

•Annotations for specific tasks (NER, sentiment, political leaning)

•Categorization by topic (e.g., elections, diplomacy, protests)

Licensing

This dataset is developed and maintained by FutureBeeAI and is available for commercial licensing. We also offer flexible terms for academic, governmental, or NGO use cases.

Use Cases

MT Engine

Language model

Predictive keyboards

Spell check

Grammar correction

Use of parallel corpus dataset in Text/speech system

Text/speech systems

Dataset Sample(s)

SAMPLE

SOURCE LANGUAGE

TARGET LANGUAGE

Bihar Chief Minister Nitish Kumar's confirmed: No more alliance with BJP forever

Today evening there is a meeting of ADMK MLAs in Chennai

Congress President Election tomorrow: 4 polling centers in Sathyamurthy Bhavan, Chennai

A.D.M.K. Golden Jubilee Anniversary: Respect to MGR, Jayalalitha Statues

Public Meetings of 51st ADMK's Annual Inaugural : Edappadi will deliver keynote speech at Namakkal on 20th

Congress President Election: Mallikarjuna Kharge resigns from Rajya Sabha post

Sudden visit to the headquarters: E.P.S. Emergency discussion with A.D.M.K. Administrators

Ghulam Nabi Azad's new party is called 'Democratic Freedom Party’

3-day hiking from Chennai to Sriperumbudur from 25th to protect Constitution: K.S. Alagiri

DMK Nominations for internal party elections have started

ATTRIBUTES

Target Language :Tamil

Source Language :English

Domain :Political

Dataset Details

Dataset Type

Text Corpus

Volume

50K+ Sentences

Media type

Text

Language Pair

English-Tamil

File Details

Type

Bilingual

Word Count

7 to 25 Words per Asset

Format

XLSX, TMX, XML, XLIFF, XLS

Annotation

Read the License Terms

Browse FAQs

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