VALIDATION.md

Validation

Methodology

Two independent samples were drawn for human validation, following a stratified sampling protocol (src/sample_for_validation.py):

• 100 claims, stratified proportionally across the six authors in the corpus (Marx/Engels, Lenin, Luxemburg, Trotsky, Stalin, Mao), out of 71,572 total.
• 50 concept-evolution edges, stratified proportionally across the seven transformation labels (EXTENDED, CONTEXTUALIZED, REFORMULATED, CONTESTED, PRESERVED, INSUFFICIENT, REJECTED), out of 446 total.

Claims were checked against a strict standard: is the claim's content actually verifiable from its cited evidence_span alone, treating anything outside that span (including background knowledge of the source text) as unverified. This is a conservative standard: it flags cases where the evidence span was truncated by an ellipsis in a way that hides the specific content the claim asserts, even if that content is accurate.

Evolution edges were checked for internal coherence (does the rationale support the assigned label) and plausibility against known Marxist intellectual history. This is a weaker check than the claims review: the validation sample provides only the IDs of the claims each rationale cites (key_earlier_claims/key_later_claims), not their text, so word-level cross-referencing against source evidence was not possible in this pass.

An initial automated pass (Claude, Anthropic) was run first, followed by human adjudication (the corpus author, a domain expert in this literature) on every case the automated pass could not resolve with confidence. This two-stage design exists because an LLM checking another LLM's extraction is not an independent check in the sense the validation protocol intends; both share similar reasoning patterns and blind spots. The domain-expert pass is what gives the final numbers below their evidentiary weight; the automated pass functioned as a fast pre-filter that surfaced candidates for review, not as a substitute for it.

Results

Sample	n	Correct	Accuracy
Claims (vs. evidence span)	100	99	99.0%
Evolution edges (rationale coherence + plausibility)	50	50	100%

5 of 150 total items were flagged as uncertain by the automated pass and resolved by human review. Of these, 4 were confirmed accurate on inspection: in each case the claim contained specific content (a name, an attribution, a causal detail) that had been elided by ... in the extracted evidence span but was in fact correct given the full source passage. This illustrates a systematic conservatism in the evidence-span-only check: it under-counts correct claims whose exact wording happens to fall outside the quoted span.

One item did not survive review:

Claim: "Political enemies repeatedly reused old accusations, shifting them from right to left without imagination." Evidence span: "they simply switched the same old accusations about from one point to another, the movement being predominantly from right to left"

The phrase "without imagination" is an evaluative addition not present in the source text, a documented instance of the extraction model supplying a plausible-sounding editorial gloss beyond what the evidence supports. This is retained in the dataset (flagged human_correct=n in the validation CSV) rather than silently corrected, since it is a genuine and informative failure mode of the pipeline, not an isolated fluke to be memory-holed.

Caveats

• Sample size. 100/71,572 claims (0.14%) and 50/446 evolution edges (11.2%) were reviewed. These are point estimates, not corpus-wide guarantees; a different random sample could yield a different figure, especially for the claims accuracy given the small absolute sample relative to corpus size.
• Confidence scores are not a reliable uncertainty signal. The 446 evolution edges have a confidence distribution with mean 0.852 and std 0.035 (75% of all edges fall between 0.85-0.86) - implausibly narrow for a model genuinely discriminating between certain and uncertain judgments. Do not filter or weight by this column as if it reflects calibrated uncertainty.
• Evolution-edge validation was weaker than claims validation, for the reason described above (no claim text in the sample, only IDs). A rigorous cross-reference against full claim text has not yet been performed at scale.
• Interpretive edges are perspectival, not objective fact. Transformation labels (especially CONTESTED/REJECTED) reflect the extraction model's reading of the cited passages, framed as a documentary+interpretive distinction (see config/ontology.yaml) rather than a canonical verdict on contested historical questions (e.g., continuity vs. rupture between Lenin and Stalin). Different scholarly traditions describe these relationships differently; the dataset records one LLM-assisted reading, evidence-linked and human-spot-checked, not a settled adjudication.
• A likely duplicate work was identified but not yet removed as of this validation pass: Trotsky's History of the Russian Revolution appears to have been ingested twice under different work_ids (a single-file edition and a separately split 3-volume edition), via independent keyword matches on the same harvested index page. src/dedupe_works.py exists to detect and remove this class of duplicate but has not yet been run against the released corpus. Downstream users should be aware that, until this is applied, Trotsky's claims on any concept discussed in that book may be double-weighted relative to other authors.