Add OpenSTEM-QA v0.1: 10,000 synthetic STEM MCQs

.gitattributes

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 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+data/train.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+pretty_name: OpenSTEM-QA
+tags:
+- stem
+- mathematics
+- physics
+- chemistry
+- synthetic
+- multiple-choice
+- jee-inspired
+task_categories:
+- question-answering
+language:
+- en
+---
+
+# OpenSTEM-QA
+
+**10,000 original, synthetic STEM multiple-choice QA records by Axilo Labz.**
+
+Hugging Face target repository: `Axilo67/openstem-qa`
+
+## Release contents
+
+- 10,000 unique question records.
+- Exactly four options (A–D) per question.
+- One designated answer option.
+- A worked numerical solution.
+- An explanation field for each option.
+- 3,340 mathematics, 3,330 physics and 3,330 chemistry questions.
+- `train` (9,000), `validation` (500) and `test` (500) JSONL splits.
+- A combined JSONL file containing all records.
+
+## Subject and topic coverage
+
+### Mathematics
+Quadratic-root identities, arithmetic and geometric progressions, polynomial differentiation, polynomial definite integrals, combinations, probability without replacement, determinants, vector dot products, and complex-number division.
+
+### Physics
+Projectile motion, work–energy, friction on an inclined plane, rotational dynamics, series-parallel circuits, Coulomb's law, capacitor energy, isochoric ideal-gas processes, thin-lens magnification, and mass–spring simple harmonic motion.
+
+### Chemistry
+Limiting reagents, ideal gases, strong-acid/strong-base mixtures, first-order kinetics, electrolysis, colligative properties, chemical equilibrium, the Nernst equation, degree of unsaturation, and formal oxidation-state charge balance in hypothetical coordination ions.
+
+## Generation method
+
+This release was generated with deterministic Python templates and randomized numerical parameters. It was **not** generated by `zai-org/GLM-5.3-Flash`. The hosted GLM model was not run because the available Hugging Face remote-compute route returned `402 Payment Required`.
+
+The questions are newly worded and parameterized. They are inspired by the subject matter and calculation style of Indian JEE preparation, but they are not official JEE questions and do not reproduce past-paper questions.
+
+## Record schema
+
+Each JSONL object contains:
+
+| Field | Meaning |
+|---|---|
+| `id` | Unique record identifier |
+| `subject`, `topic`, `subtopic` | Curriculum labels |
+| `difficulty` | Provisional `hard` or `very_hard` label |
+| `difficulty_labeling_method`, `difficulty_note` | Explain the provisional label |
+| `question_type` | `single_correct_mcq` |
+| `question` | Question statement |
+| `options` | Exactly four choices keyed A–D |
+| `correct_answer` | Correct option label |
+| `correct_answer_value` | Numeric answer with units where applicable |
+| `solution` | Worked calculation |
+| `option_explanations` | Explanation for all four choices |
+| `concepts_required` | Concept tags |
+| `reasoning_steps` | Template-declared step count |
+| `answer_type`, `language` | Answer format and language |
+| `origin`, `source_type` | Synthetic-data provenance |
+| `generator`, `generator_template_id` | Generator and question family |
+| `verification_status`, `verification_note`, `answer_validation` | Validation provenance and limitations |
+
+## Validation performed
+
+The generated release passed these structural checks:
+
+- Exactly 10,000 rows.
+- 10,000 unique IDs.
+- 10,000 unique question strings after basic punctuation/case normalization.
+- Exactly four option keys per record (A, B, C, D).
+- Four distinct option strings per record.
+- The `correct_answer` label points to the option that matches `correct_answer_value`.
+- A non-empty question and worked solution.
+- An explanation field for every option.
+- Exact split sizes: 9,000 / 500 / 500.
+- Balanced subject representation across splits.
+
+The validation report is included as `quality_report.json`.
+
+## Important limitations
+
+1. **Not expert-reviewed:** Structural checks confirm schema and answer-key consistency. They do not replace an independent subject-matter solution review.
+2. **Difficulty is provisional:** This release labels records `hard` or `very_hard` by question-template family. It does not claim examiner-calibrated JEE Advanced difficulty. No records are labeled `ultra_hard` in v0.1 because the current template set does not justify that claim.
+3. **Parameterized families:** The 10,000 rows come from 30 underlying templates. Values and wording vary, but solution structures repeat. This is not equivalent to 10,000 independently authored problems.
+4. **Evaluation leakage:** The same template families appear in train, validation and test. The validation/test splits are useful for basic pipeline checks, but should not be treated as template-generalization benchmarks.
+5. **Numeric emphasis:** Most questions are calculation-based. Proof-based mathematics, multi-select questions, assertion-reason questions, qualitative chemistry, organic reaction mechanisms, and experimental-data interpretation are limited or absent.
+6. **Distractors:** Incorrect numerical options are distinct alternatives. Their explanations generally identify the computed value rather than diagnosing a specific misconception.
+7. **Licensing:** No separate reuse license is asserted in this seed release. A formal license should be selected before third-party redistribution or commercial use.
+
+## Loading
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset(
+    "json",
+    data_files={
+        "train": "data/train.jsonl",
+        "validation": "data/validation.jsonl",
+        "test": "data/test.jsonl",
+    },
+)
+print(ds)
+```
+
+To use a single combined file:
+
+```python
+from datasets import load_dataset
+ds = load_dataset("json", data_files="openstem_qa_v0.1.jsonl", split="train")
+```
+
+## Intended use
+
+Useful for experiments in STEM question answering, numeric MCQ supervision, answer extraction and worked-solution training. Independently review examples before using them in high-stakes educational settings.
+
+**Axilo Labz — Exploring Intelligence. Engineering Possibilities.**

SHA256SUMS.txt

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data/train.jsonl

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dataset_info.json

@@ -0,0 +1,36 @@
+{
+  "name": "OpenSTEM-QA",
+  "version": "0.1.0",
+  "hub_repository": "Axilo67/openstem-qa",
+  "rows": 10000,
+  "splits": {
+    "train": 9000,
+    "validation": 500,
+    "test": 500
+  },
+  "subjects": {
+    "mathematics": 3340,
+    "physics": 3330,
+    "chemistry": 3330
+  },
+  "difficulty": {
+    "hard": 6001,
+    "very_hard": 3999
+  },
+  "template_families": 30,
+  "generation": {
+    "method": "deterministic parameterized Python templates with randomized numerical parameters",
+    "model": "none",
+    "requested_model": "zai-org/GLM-5.3-Flash",
+    "requested_model_used": false
+  },
+  "license": "not specified",
+  "limitations": [
+    "not expert reviewed",
+    "difficulty not examiner calibrated",
+    "30 repeated template families",
+    "template family leakage across splits",
+    "numeric calculation bias",
+    "generic distractor rationales"
+  ]
+}

quality_report.json

@@ -0,0 +1,72 @@
+{
+  "total_rows": 10000,
+  "unique_ids": 10000,
+  "unique_questions_after_normalization": 10000,
+  "structural_issues": 0,
+  "first_issues": [],
+  "split_counts": {
+    "train": 9000,
+    "validation": 500,
+    "test": 500
+  },
+  "split_subject_counts": {
+    "train": {
+      "physics": 2997,
+      "chemistry": 2997,
+      "mathematics": 3006
+    },
+    "validation": {
+      "physics": 167,
+      "mathematics": 167,
+      "chemistry": 166
+    },
+    "test": {
+      "mathematics": 167,
+      "chemistry": 167,
+      "physics": 166
+    }
+  },
+  "subject_counts": {
+    "mathematics": 3340,
+    "physics": 3330,
+    "chemistry": 3330
+  },
+  "difficulty_counts": {
+    "hard": 6001,
+    "very_hard": 3999
+  },
+  "topic_counts": {
+    "algebra": 334,
+    "sequences_and_series": 668,
+    "calculus": 668,
+    "combinatorics": 334,
+    "probability": 334,
+    "linear_algebra": 334,
+    "vectors": 334,
+    "complex_numbers": 334,
+    "mechanics": 999,
+    "rotational_mechanics": 333,
+    "electricity": 333,
+    "electrostatics": 666,
+    "thermodynamics": 333,
+    "ray_optics": 333,
+    "oscillations": 333,
+    "stoichiometry": 333,
+    "physical_chemistry": 2331,
+    "organic_chemistry": 333,
+    "inorganic_chemistry": 333
+  },
+  "template_family_count": 30,
+  "checks": {
+    "exact_10000_rows": true,
+    "unique_ids": true,
+    "unique_questions": true,
+    "exactly_four_options": true,
+    "four_distinct_options": true,
+    "correct_answer_matches_value": true,
+    "four_option_explanations": true,
+    "nonempty_questions_and_solutions": true,
+    "90_5_5_split": true
+  },
+  "verification_scope": "The answer is produced by the explicit formula encoded in each generator template. Structural and answer-key alignment were checked; no independent subject-matter expert review was performed."
+}

validate_dataset.py

@@ -0,0 +1,21 @@
+#!/usr/bin/env python3
+import json, sys
+from pathlib import Path
+
+def check(path):
+    rows=[json.loads(line) for line in Path(path).open(encoding="utf-8") if line.strip()]
+    ids=set()
+    for n,row in enumerate(rows,1):
+        assert row["id"] not in ids, f"duplicate id at line {n}"
+        ids.add(row["id"])
+        assert set(row["options"]) == {"A","B","C","D"}, f"bad options at line {n}"
+        assert len(set(row["options"].values())) == 4, f"duplicate options at line {n}"
+        assert row["correct_answer"] in "ABCD", f"bad answer label at line {n}"
+        assert row["options"][row["correct_answer"]] == row["correct_answer_value"], f"answer mismatch at line {n}"
+        assert set(row["option_explanations"]) == {"A","B","C","D"}, f"missing option explanation at line {n}"
+        assert row["question"].strip() and row["solution"].strip(), f"empty question/solution at line {n}"
+    print(f"{path}: {len(rows)} records passed structural checks")
+
+if __name__ == "__main__":
+    for p in sys.argv[1:]:
+        check(p)