Bosnian CORE NLP Standard (BCS-compatible): Text Normalization & Tokenization — v1.1-LTS
**Bosnian CORE NLP Standard (BCS-compatible) v1.1-LTS** is a deterministic and audit-ready specification for the normalization, sentence segmentation, tokenization, and quantitative measurement of Bosnian Latin-script text. The release combines a formal specification with an executable reference implementation (`bcscore`) written in pure Python ≥ 3.9 and a byte-exact conformance suite containing 118 test cases. Version 1.1-LTS supersedes v1.0-LTS and resolves a set of specification ambiguities and inconsistencies, including handling of ZWJ characters, dashes, abbreviation lists, case folding, segmentation order, and n-gram reset behavior. The release introduces explicit character-stream profiles (`CHAR-LS`, `CHAR-L`, `CHAR-NWS`, `CHAR-FULL`) and machine-readable measurement profiles intended to make quantitative NLP and information-theoretic results reproducible and comparable. Annex M defines the supported quantitative measures, including Shannon entropy, Miller–Madow correction, Onicescu energy, Rényi entropy, Gini–Simpson index, HHI, Jensen–Shannon divergence, Zipf analysis, and Heaps analysis, together with required sampling diagnostics. Annex P documents the ENT-2025 measurement profile used for the published information-theoretic analysis of Bosnian. The release also includes reproducibility mechanisms such as content-derived `run_id` values, `SOURCE_DATE_EPOCH`, deterministic summation, JSON Schemas, and `verify-run`. **Supersedes:** v1.0-LTS — https://doi.org/10.5281/zenodo.18570562 **Author:** Hasan Kahrimanović Hyper Efficient System LLC ORCID: https://orcid.org/0009-0005-1746-4498 **Licensing:** Specification and specification assets: CC BY 4.0. Reference implementation: MIT License.
Authors
- Hasan Kahrimanovic
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-30
- DOI
- https://doi.org/10.5281/zenodo.23049395
- Primary Topic
- Natural Language Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00