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Adesh C S

NL-to-SQL Annotation & Dataset Builder — Academic Project

INDIA flag
banglore, India
$15.00/hrEntry LevelHivemindLabel Studio

Key Skills

Software

HiveMindHiveMind
Label StudioLabel Studio

Top Subject Matter

Natural Language Processing
SQL schema mapping
LLM fine-tuning dataset creation

Top Data Types

TextText
ImageImage

Top Task Types

Classification
Data Collection

Freelancer Overview

NL-to-SQL Annotation & Dataset Builder — Academic Project. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Engineering, Bapuji Institute of Engineering & Technology, Visvesvaraya Technological University (2026). AI-training focus includes data types such as Text and Image and labeling workflows including Classification and Data Collection.

Entry LevelEnglish

Labeling Experience

NL-to-SQL Annotation & Dataset Builder — Academic Project

OtherTextClassification
I designed and labeled a corpus of over 500 natural language queries, mapping them to structured SQL ground truths. The annotation involved intent recognition and schema-mapping, with rigorous quality control performed throughout the data pipeline. Project outcomes were validated through publication and dataset preparation for AI training tasks. • Query intent classes were labeled as SELECT, INSERT, JOIN, and aggregate. • Entity mentions in text were tagged to support schema mapping and structured output. • Ground-truth data for instruction-following tasks was created for LLM fine-tuning. • Annotation quality was ensured through systematic reviews and publication of methodology.

I designed and labeled a corpus of over 500 natural language queries, mapping them to structured SQL ground truths. The annotation involved intent recognition and schema-mapping, with rigorous quality control performed throughout the data pipeline. Project outcomes were validated through publication and dataset preparation for AI training tasks. • Query intent classes were labeled as SELECT, INSERT, JOIN, and aggregate. • Entity mentions in text were tagged to support schema mapping and structured output. • Ground-truth data for instruction-following tasks was created for LLM fine-tuning. • Annotation quality was ensured through systematic reviews and publication of methodology.

2024 - 2025

Crowdsource Data Collection Platform (FixChain) — Blockchain Project

OtherImageData Collection
I designed the schema and categorized user-submitted images and metadata for a civic issue reporting platform. An annotation framework for issue types was developed to simulate real-world taxonomy for AI training datasets. This provided experience in multi-modal data ingestion and structuring annotated image datasets for downstream ML tasks. • Mapped and structured images with related metadata for annotation. • Defined classes for civic issues such as potholes, waste, and infrastructure. • Developed the annotation schema for realistic labeling taxonomy. • Built foundational datasets supporting further ML model training.

I designed the schema and categorized user-submitted images and metadata for a civic issue reporting platform. An annotation framework for issue types was developed to simulate real-world taxonomy for AI training datasets. This provided experience in multi-modal data ingestion and structuring annotated image datasets for downstream ML tasks. • Mapped and structured images with related metadata for annotation. • Defined classes for civic issues such as potholes, waste, and infrastructure. • Developed the annotation schema for realistic labeling taxonomy. • Built foundational datasets supporting further ML model training.

2024 - 2024

Semantic Search & Text Similarity Labeler — Academic Project

OtherTextClassification
I built and hand-labeled a document relevance dataset for semantic search and text similarity tasks. Each sentence pair was manually reviewed and annotated for semantic equivalence and retrieval relevance, implementing industry standard evaluation methods. Annotation consistency and data validity were maintained through systematic review processes and agreement metrics. • Labeled positive and negative similarity pairs using cosine similarity thresholding. • Evaluated inter-annotator agreement for dataset reliability. • Indexed labeled datasets for semantic retrieval benchmarking. • Applied industry-standard evaluation workflows for relevance labels.

I built and hand-labeled a document relevance dataset for semantic search and text similarity tasks. Each sentence pair was manually reviewed and annotated for semantic equivalence and retrieval relevance, implementing industry standard evaluation methods. Annotation consistency and data validity were maintained through systematic review processes and agreement metrics. • Labeled positive and negative similarity pairs using cosine similarity thresholding. • Evaluated inter-annotator agreement for dataset reliability. • Indexed labeled datasets for semantic retrieval benchmarking. • Applied industry-standard evaluation workflows for relevance labels.

2024 - 2024

Education

B

Bapuji Institute of Engineering & Technology, Visvesvaraya Technological University

Bachelor of Engineering, Computer Science and Engineering

Bachelor of Engineering
2022 - 2026

Work History

B

Bapuji Institute of Engineering & Technology, VTU

B.E. in Computer Science & Engineering

Location not specified
2022 - 2026
A

Academic Project

NL-to-SQL Annotation & Dataset Builder

Location not specified
2024 - 2025