--- license: cc-by-4.0 language: - en tags: - knowledge-graph - intellectual-history - marxism - political-philosophy - computational-humanities - temporal-graph task_categories: - text-classification - graph-ml pretty_name: MarxGraph size_categories: - 10K` edges. ### Transformation labels Each `concept_evolution` row classifies how a concept changed between two chronologically-ordered thinkers: - `PRESERVED`: restated with essentially the same content and scope - `EXTENDED`: same core meaning, new components or scope added - `REFORMULATED`: same term, different core content or theoretical role - `CONTEXTUALIZED`: adapted to new historical/national conditions - `CONTESTED`: later thinker explicitly argues against the earlier treatment - `REJECTED`: concept abandoned or repudiated - `INSUFFICIENT`: evidence too thin to support any label (the model declines to force a verdict rather than fabricate one) Distribution across the 446 edges: 76.0% EXTENDED, 10.1% CONTEXTUALIZED, 6.3% REFORMULATED, 4.7% CONTESTED, 2.0% PRESERVED, 0.7% INSUFFICIENT, 0.2% REJECTED. ## Construction Built with a five-stage pipeline (full code included): EPUB download → passage segmentation → LLM claim/mention/reference extraction → LLM concept-transformation typing (constrained to a documented set of plausible lineage pairs) → graph assembly. Primary extraction model: `openai/gpt-oss-120b` via Groq. See `README.md` in the code repository for the full pipeline and `config/ontology.yaml` for the entity/relation schema. ## Validation 100 claims and 50 evolution edges were checked against a stratified sample protocol, with an automated first pass followed by domain-expert human adjudication of every uncertain case. **Result: 99% claims accuracy (99/100), 100% evolution-edge coherence (50/50)** on the reviewed sample. Full methodology, including the one documented failure case and important caveats about sample size and the narrowness of the model's confidence scores, is in [`VALIDATION.md`](VALIDATION.md); please read it before citing accuracy figures out of context. ## Known limitations - **Confidence scores are not calibrated.** Evolution-edge confidence values cluster tightly (mean 0.852, std 0.035) and should not be used as a reliability filter. - **A likely duplicate work has not yet been removed.** Trotsky's *History of the Russian Revolution* appears to be ingested twice (single-file and 3-volume editions), inflating Trotsky's claim counts on affected concepts. A deduplication tool (`src/dedupe_works.py`) exists but has not been applied to this release. - **Interpretive edges are one LLM-assisted reading, not a canonical verdict.** Especially for ideologically contested relationships (e.g., Stalin's relationship to Lenin, or Trotsky's to Stalin), different traditions characterize continuity/rupture differently. Treat `CONTESTED`/`REJECTED` labels as a documented, evidence-linked interpretation, open to challenge, not as settled historiography. - **Extraction quality reflects the extraction model.** `openai/gpt-oss-120b` is far smaller than frontier models; the validation pass documents at least one case of the model adding a plausible but unsupported evaluative gloss to an otherwise accurate paraphrase. - **Licensing is mixed at the work level.** `works.parquet.license` marks each work `pd` (public domain, safe to redistribute as text) or `verify` (check the specific translation/edition's copyright status on MIA before redistributing raw text; this applies especially to some Stalin, Mao, and Luxemburg translations). Annotations (claims, relations, evolution edges) are original analysis and released under this dataset's license regardless of source-text status. ## Citation If you use MarxGraph, please cite the dataset directly: ``` Bose, J. (2026). MarxGraph: A Temporal Knowledge Graph of Marxist Intellectual History [Dataset]. Hugging Face. https://huggingface.co/datasets/ ``` ## Credits Source texts: [Marxists Internet Archive](https://www.marxists.org), a volunteer-run archive; please support their work if you can. Dataset construction, ontology design, and validation: Joy Bose (joy.bose@ieee.org).