Corpus and coding record for: Word Embedding Techniques in NLP: A Comprehensive Review and Historical Perspective

Supporting data for "Word Embedding Techniques in Natural Language Processing: A Comprehensive Review and Historical Perspective" (Expert Systems with Applications). The paper's central claim is a negative one: the movement of word embeddings from standalone research output to internal system layer is a continuous accumulation rather than a watershed. Fitting year continuously shows sustained change, with the share of techniques that are variants rather than distinct proposals rising at an odds ratio of 19.5 per decade and team size at 1.7, yet of four candidate breakpoints (Transformer, BERT, GPT-3, ChatGPT) none improves on the smooth trend for five of seven outcomes, and each surviving result breaks at a different year. That claim is only as good as the corpus it is measured on, because a corpus assembled by search would carry the field's own assumptions about which years mattered into the result. The corpus here is therefore built by a stated rule rather than by search: 30 seed reviews, expanded to a register of 95 techniques and 134 anchor papers, under a written protocol fixed before screening began. This deposit is the record of every decision that rule produced. Contents: the protocol with every query as executed; the codebook with its binding worked examples; a run log carrying every count the manuscript reports, one row per screening stage; the coded technique register and corpus manifest; and the analysis scripts that re-derive every reported quantity from them offline. Any count in the paper traces to a row of run_log.csv, and any technique-level code to its row in the register with the coder's note attached. This is a systematized review (Grant & Booth), not a systematic review, and the protocol was fixed prior to screening, not pre-registered. Full-text PDFs are not redistributed (copyright); every paper is identified by DOI or OpenAlex id in data/corpus_manifest.csv.