{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/code/get-vocabs","entry":"get_vocabs","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":5,"n_papers_ran":1,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":5,"n_samples_ran":2,"n_samples_fingerprinted":0,"n_places":7,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":2,"unverified":3},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2408.11853","paper":"/paper/pymarian-fast-neural-machine-translation-and","title":"PyMarian: Fast Neural Machine Translation and Evaluation in Python","date":"2024-08-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"OpenNMT/CTranslate2","path":"python/ctranslate2/converters/eole_ct2.py","file_url":"https://github.com/OpenNMT/CTranslate2/blob/HEAD/python/ctranslate2/converters/eole_ct2.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"57d2b237f2f6c212","mcp_get_code":{"code_sha256":"57d2b237f2f6c212"}},{"arxiv_id":"2408.11853","paper":"/paper/pymarian-fast-neural-machine-translation-and","title":"PyMarian: Fast Neural Machine Translation and Evaluation in Python","date":"2024-08-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"OpenNMT/CTranslate2","path":"python/ctranslate2/converters/opennmt_py.py","file_url":"https://github.com/OpenNMT/CTranslate2/blob/HEAD/python/ctranslate2/converters/opennmt_py.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"794ef6f28819556a","mcp_get_code":{"code_sha256":"794ef6f28819556a"}},{"arxiv_id":"2010.12777","paper":"/paper/improving-multilingual-models-with-language","title":"Improving Multilingual Models with Language-Clustered Vocabularies","date":"2020-10-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"afshinrahimi/mmner","path":"config.py","file_url":"https://github.com/afshinrahimi/mmner/blob/HEAD/config.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"384baa37e7d09ae3","mcp_get_code":{"code_sha256":"384baa37e7d09ae3"}},{"arxiv_id":"1603.01360","paper":"/paper/neural-architectures-for-named-entity","title":"Neural Architectures for Named Entity Recognition","date":"2016-03-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"guillaumegenthial/sequence_tagging","path":"model/data_utils.py","file_url":"https://github.com/guillaumegenthial/sequence_tagging/blob/HEAD/model/data_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"384baa37e7d09ae3","mcp_get_code":{"code_sha256":"384baa37e7d09ae3"}},{"arxiv_id":"1603.01360","paper":"/paper/neural-architectures-for-named-entity","title":"Neural Architectures for Named Entity Recognition","date":"2016-03-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"riedlma/sequence_tagging","path":"model/data_utils.py","file_url":"https://github.com/riedlma/sequence_tagging/blob/HEAD/model/data_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"3a2be4774b779b43","mcp_get_code":{"code_sha256":"3a2be4774b779b43"}},{"arxiv_id":"1603.01354","paper":"/paper/end-to-end-sequence-labeling-via-bi","title":"End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF","date":"2016-03-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"SenticNet/aspect-extraction","path":"model/data_utils.py","file_url":"https://github.com/SenticNet/aspect-extraction/blob/HEAD/model/data_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"384baa37e7d09ae3","mcp_get_code":{"code_sha256":"384baa37e7d09ae3"}},{"arxiv_id":"2024.findings-emnlp.944","paper":null,"title":"arXiv:2024.findings-emnlp.944","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"jind11/HSLN-Joint-Sentence-Classification","path":"model/data_utils.py","file_url":"https://github.com/jind11/HSLN-Joint-Sentence-Classification/blob/HEAD/model/data_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f52141cb2c938800","mcp_get_code":{"code_sha256":"f52141cb2c938800"}}]}