Somtharu181coder/educational_vedantu_FAQs_Nepali_sft_dataset

Vedantu CUET FAQs — Nepali SFT Dataset

A single-turn instruction-following (Q&A) dataset in Nepali, built from Vedantu's CUET (Common University Entrance Test) 2026 FAQ page. The dataset is formatted for supervised fine-tuning (SFT) in a conversations-style chat schema.

Summary

How this dataset was built

1. 1.Merge — Two raw scrapes of the same Vedantu FAQ page were combined:

1. 1.Semantic review & cleaning
2. 2.Removed 75 rejected entries that were exact duplicates of content already captured elsewhere (repeat scraping passes).
3. 3.Deduplicated the remaining pool by normalized question text.
4. 4.Manually inspected and dropped entries where the question/answer boundary had clearly shifted during scraping (e.g. a question about "NTA Score Validity" paired with an unrelated answer about "DigiLocker") — a scraping artifact, not a real FAQ.
5. 5.Repaired run-together text caused by missing whitespace in scraped tables/lists (e.g. PwD categories, exam-pattern tables, admit-card detail lists).
6. 6.Result: 49 clean, unique, correctly-paired Q&A items.

1. 1.Translation — Each Q&A pair was translated from English into natural, formal Nepali (Devanagari script), preserving exam-specific terms (NTA, CUET, PwD, DigiLocker, etc.) where an English acronym is the standard term used by Nepali speakers as well.

1. 1.Formatting — Records were converted into the target SFT schema (see below). The schema's structure was reused as specified; field values were populated to accurately describe this dataset rather than copied from any reference example.

Schema

Each record is a JSONL object:

  "id": "sg_<32-char hash>",
  "conversations": [
    { "from": "human", "value": "<question in Nepali>" },
    { "from": "gpt",   "value": "<answer in Nepali>" }
  ],
  "source": "vedantu/cuet_faqs:merged:train",
  "source_name": "vedantu_cuet_faqs_nepali",
  "source_repo": "vedantu/cuet_faqs",
  "source_config": "merged",
  "source_split": "train",
  "source_revision": "local-merge-2026-09-07",
  "source_row_id": "vedantu:cuet_faqs:merged:<n>",
  "language": "ne",
  "language_code": "npi",
  "script": "Deva",
  "license": "Unspecified",
  "license_tier": "unspecified",
  "task_type": "instruction-following",
  "generation_type": "machine-translated",
  "condition": "web-scraped,machine-translated",
  "url": "https://www.vedantu.com/cuet/cuet-faqs",
  "metadata_json": "{ ...see below... }"

Field notes

• —`id` — Stable synthetic ID (sg_ + MD5 hash of the record index and original English question). Unique per row.
• —`conversations` — Exactly one human turn (the question) and one human turn (the answer). No multi-turn dialogue.
• —`source` / `source_name` / `source_repo` / `source_config` / `source_split` — Provenance identifiers for this merged/translated build; not a published HF dataset.
• —`source_revision` — Local build tag, since this isn't pinned to a versioned upstream repo.
• —`source_row_id` — Sequential row identifier within this merge (vedantu:cuet_faqs:merged:<n>).
• —`language` / `language_code` / `script` — Nepali, ISO 639-3 npi, Devanagari.
• —`license` / `license_tier` — license: cc-by-4.0 and license_tier: permissive
• —`task_type` — instruction-following, consistent with single-turn FAQ-style Q&A.
• —`generation_type` — machine-translated: the underlying FAQ content is human-authored (scraped), but the Nepali text was produced by machine translation, not by a human Nepali speaker.
• —`condition` — web-scraped,machine-translated, describing the full provenance chain.
• —`url` — Original source page for all records.
• —`metadata_json` — A JSON-encoded string containing:
• —domain: "education"
• —category: "CUET"
• —original_language: "English"
• —original_question / original_answer: the source English text, kept for traceability/back-translation checks
• —merge_note: brief description of the merge/cleaning process

Known limitations

• —Machine translation, not human-reviewed Nepali. Spot-check before using for anything user-facing; exam terminology (fee amounts, dates, section names) should be verified against an authoritative CUET source before relying on it for real guidance.
• —Time-sensitive content. Several answers contain exam-cycle-specific details (fees, dates, correction windows) tied to the "2026" cycle referenced on the source page. These will go stale and should not be treated as current CUET information.
• —Not de-duplicated against other datasets. Only internal duplication (between the accepted/rejected scrape files) was removed.
• —Single-turn only. No multi-turn conversations, follow-ups, or clarification exchanges.
• —Answer length varies widely (~40–1,300 characters) — a few answers (e.g. the CUET 2026 exam-pattern breakdown) are long, table-derived explanations rather than short FAQ answers.

Suggested uses

• —Fine-tuning or evaluating Nepali-language instruction-following models on short factual Q&A.
• —Domain-adaptation for education/exam-assistant use cases in Nepali.
• —As a small seed set to bootstrap a larger Nepali CUET/exam-FAQ corpus (e.g. combined with other exam boards or translated into additional South Asian languages).

File

• —vedantu_cuet_faqs_nepali_sft.json — 49 records, UTF-8 JSON array, ~1,470 lines pretty-printed.