ROUGE concept
| Definition | A family of scores for generated text against a reference. Chapter 0 section 0.11. |
|---|---|
| Example | A generated text that reproduces 6 of a reference’s 8 unigrams has ROUGE-1 recall 0.75. |
| Book | Data Mining as Observation, draft 0.2, commit f3914f0; entry id rouge, kind concept. |
| Status | no ledger row names this entry. Corrections: none recorded. |
| Defining equation | none |
| Assumptions and scope |
|
| Prior art | none recorded |
| Evidence | turboquant-pro/CLAIMS.md:63-81, turboquant-pro/benchmarks/kvquant_matrix/REVAL-2026-08-08.md, lean/DataMiningAsObservation/Rouge.lean |
| Reviewed | not yet reviewed; generated 2026-09-10 from records at the commits on the provenance page. |
Equation
none
Conditions
- A family of scores for generated text against a reference. ROUGE-1 recall counts the reference’s words the candidate contains, with multiplicity, over the reference’s length. It lies in the unit interval, is one for the reference itself, and is one for any rearrangement of the reference, since it reads bags and not order.
- A ROUGE score therefore certifies less than it seems to. The 13.7 ROUGE-L difference at 512 tokens re-validated at negative 0.31 on forty documents, and the claims ledger carries both numbers.
Conditions are curated in entries.toml rather than read
from a record.
Ledger
none
First stated
Lin, ROUGE, 2004, as chapter 0 section 0.11 states it, with the
program’s 13.7 ROUGE-L number and its re-validation in
turboquant-pro/CLAIMS.md:63-81.
Measurements
| Where the book states it | Numbers, as the book’s sources table records them | Source |
|---|---|---|
| chapter 8 section 8.9 | 13.7 ROUGE-L, 0.25/4.19/9.60/13.7 at 64/128/256/512, re-validation
negative 0.31 n=40, 26.64 under symmetric nf4,
_quant_nf4a_group unchanged since 289bdfc
before 4f7baab |
turboquant-pro/CLAIMS.md:63-81;
turboquant-pro/benchmarks/kvquant_matrix/REVAL-2026-08-08.md |
Failures and corrections
none
Invariance envelope
none declared
Machine checked
lean/DataMiningAsObservation/Rouge.lean,
theorems overlap_le, rouge1_mem_unit,
rouge1_self, rouge1_perm, at
observation-data-mining f3914f0; what the check covers is stated in the
book’s appendix
C.
Used in
Data Mining as Observation chapters 0, 8.
Related
bag of words; perplexity; harness; certificate.
See also
Book equations stated beside the entry’s terms, not defining it: 0.22.
Ledger rows that cite the entry’s records without naming it: NEG-4.
Status
Generated 2026-09-10 by encyclopedia/generate.py; book
at observation-data-mining f3914f0; the commit of every record is listed
in the encyclopedia’s provenance.