{"id":"https://openalex.org/W7164031046","doi":"https://doi.org/10.48550/arxiv.2606.08715","title":"Operationalizing Linguistic Methods through Prompt-Engineering Skills: An Automatic Chinese Web Neologism Detection Pipeline","display_name":"Operationalizing Linguistic Methods through Prompt-Engineering Skills: An Automatic Chinese Web Neologism Detection Pipeline","publication_year":2026,"publication_date":"2026-06-07","ids":{"openalex":"https://openalex.org/W7164031046","doi":"https://doi.org/10.48550/arxiv.2606.08715"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.08715","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08715","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.08715","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138209304","display_name":"Yufeng Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Yufeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5064908921","display_name":"Meichun Liu","orcid":"https://orcid.org/0000-0001-9471-7181"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Meichun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.7303000092506409,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.7303000092506409,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12353","display_name":"Lexicography and Language Studies","score":0.04349999874830246,"subfield":{"id":"https://openalex.org/subfields/1203","display_name":"Language and Linguistics"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14006","display_name":"Linguistics, Language Diversity, and Identity","score":0.04259999841451645,"subfield":{"id":"https://openalex.org/subfields/1203","display_name":"Language and Linguistics"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.6700999736785889},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.4828999936580658},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.45739999413490295},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.44279998540878296},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.40470001101493835},{"id":"https://openalex.org/keywords/computational-linguistics","display_name":"Computational linguistics","score":0.32910001277923584},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.31049999594688416},{"id":"https://openalex.org/keywords/latent-semantic-analysis","display_name":"Latent semantic analysis","score":0.30959999561309814},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.3061999976634979}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6948999762535095},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6761000156402588},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.6700999736785889},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6365000009536743},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.4828999936580658},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.45739999413490295},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.44279998540878296},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.40470001101493835},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.30959999561309814},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3052999973297119},{"id":"https://openalex.org/C7797323","wikidata":"https://www.wikidata.org/wiki/Q3798612","display_name":"Pointwise mutual information","level":3,"score":0.30300000309944153},{"id":"https://openalex.org/C93285893","wikidata":"https://www.wikidata.org/wiki/Q130989","display_name":"Neologism","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C9354725","wikidata":"https://www.wikidata.org/wiki/Q286017","display_name":"Operationalization","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C138954614","wikidata":"https://www.wikidata.org/wiki/Q9192","display_name":"Mandarin Chinese","level":2,"score":0.2888000011444092},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2833000123500824},{"id":"https://openalex.org/C203005215","wikidata":"https://www.wikidata.org/wiki/Q79798","display_name":"Machine translation","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C2780276568","wikidata":"https://www.wikidata.org/wiki/Q191928","display_name":"Polysemy","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C53893814","wikidata":"https://www.wikidata.org/wiki/Q7378909","display_name":"Rule-based machine translation","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C2777946921","wikidata":"https://www.wikidata.org/wiki/Q7449044","display_name":"Semantic analysis (machine learning)","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.08715","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08715","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.08715","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.08715","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8321713805198669}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,169],"present":[1],"a":[2,32,37,46,84,162],"method":[3,20,69],"for":[4],"automatic":[5],"Chinese":[6,42],"web":[7],"neologism":[8],"detection":[9],"that":[10,53,141],"operationalizes":[11],"traditional":[12],"linguistic":[13,167],"identification":[14],"principles":[15],"as":[16,123,178],"prompt-engineering":[17],"skills.":[18],"The":[19],"has":[21],"four":[22],"stages:":[23],"tokenizer-independent":[24],"character":[25],"n-gram":[26],"candidate":[27,115],"generation;":[28],"dictionary":[29],"anchoring":[30],"with":[31],"Pointwise":[33],"Mutual":[34],"Information":[35],"pre-filter;":[36],"well-formedness":[38,144],"skill":[39,52,145,154],"based":[40],"on":[41],"word-formation":[43],"principles;":[44],"and":[45,49,57,117,128,175],"combined":[47],"rule":[48],"three-way":[50],"classification":[51],"distinguishes":[54],"neologism,":[55],"entity,":[56],"none.":[58],"Applied":[59,104],"to":[60,105],"the":[61,68,80,91,98,110,124,142,151,171],"BAAI":[62],"CCI":[63],"3.0":[64],"corpus":[65],"(267M":[66],"documents),":[67],"produces":[70],"226,959":[71],"classified":[72],"candidates":[73],"including":[74],"4,853":[75],"labeled":[76],"neologisms.":[77],"To":[78],"evaluate":[79],"method,":[81,172],"we":[82],"develop":[83],"per-stage":[85],"conditional":[86,102],"recall":[87,94],"decomposition":[88,111],"in":[89],"which":[90],"pipeline's":[92],"strict":[93],"factors":[95],"mathematically":[96],"into":[97],"product":[99],"of":[100,165],"stage":[101],"recalls.":[103],"Hou":[106],"(2023)":[107],"(4,199":[108],"entries),":[109],"exposes":[112],"Stage":[113,118],"1":[114],"coverage":[116],"4B":[119],"LLM":[120],"semantic":[121,152],"judgment":[122],"two":[125],"bottlenecks":[126],"(R=41.5%":[127],"60.0%":[129],"respectively),":[130],"while":[131],"intermediate":[132],"stages":[133],"are":[134],"near-lossless.":[135],"A":[136],"length-stratified":[137],"analysis":[138],"further":[139],"reveals":[140],"structural":[143],"is":[146,155],"length-invariant":[147],"(>=":[148],"96.9%)":[149],"whereas":[150],"novelty-classification":[153],"length-dependent":[156],"(65.6%/59.0%/44.1%":[157],"across":[158],"2/3/4-character":[159],"candidates),":[160],"mapping":[161],"current":[163],"boundary":[164],"skill-based":[166],"operationalization.":[168],"release":[170],"pipeline":[173],"outputs,":[174],"evaluation":[176],"protocol":[177],"public":[179],"resources.":[180]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-10T00:00:00"}