{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:XJYGTX6ITVPAFITEQUSD3G2CLZ","short_pith_number":"pith:XJYGTX6I","canonical_record":{"source":{"id":"2606.08715","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-07T16:13:06Z","cross_cats_sorted":[],"title_canon_sha256":"4ce3fbd3035c13a011036c8fd7a1d9bba917aa0ec816c6725dfab448ef77b4a2","abstract_canon_sha256":"9f3f8a2e4bebdd7ee7dff5852a628d8a6628e69012dabea0800727ce46f1753c"},"schema_version":"1.0"},"canonical_sha256":"ba7069dfc89d5e02a26485243d9b425e75f412a767189bbb4179af26bc4c48e1","source":{"kind":"arxiv","id":"2606.08715","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.08715","created_at":"2026-06-09T01:05:48Z"},{"alias_kind":"arxiv_version","alias_value":"2606.08715v1","created_at":"2026-06-09T01:05:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.08715","created_at":"2026-06-09T01:05:48Z"},{"alias_kind":"pith_short_12","alias_value":"XJYGTX6ITVPA","created_at":"2026-06-09T01:05:48Z"},{"alias_kind":"pith_short_16","alias_value":"XJYGTX6ITVPAFITE","created_at":"2026-06-09T01:05:48Z"},{"alias_kind":"pith_short_8","alias_value":"XJYGTX6I","created_at":"2026-06-09T01:05:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:XJYGTX6ITVPAFITEQUSD3G2CLZ","target":"record","payload":{"canonical_record":{"source":{"id":"2606.08715","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-07T16:13:06Z","cross_cats_sorted":[],"title_canon_sha256":"4ce3fbd3035c13a011036c8fd7a1d9bba917aa0ec816c6725dfab448ef77b4a2","abstract_canon_sha256":"9f3f8a2e4bebdd7ee7dff5852a628d8a6628e69012dabea0800727ce46f1753c"},"schema_version":"1.0"},"canonical_sha256":"ba7069dfc89d5e02a26485243d9b425e75f412a767189bbb4179af26bc4c48e1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-09T01:05:48.085306Z","signature_b64":"gyjhyVLnBwWcYJdh+0/d0iJl6VPnQlm0b7UT4PbX9xxEPRXmTF5vt1l/EAggaCgUPD/55bVsrIZZwDdx9O6iDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ba7069dfc89d5e02a26485243d9b425e75f412a767189bbb4179af26bc4c48e1","last_reissued_at":"2026-06-09T01:05:48.084913Z","signature_status":"signed_v1","first_computed_at":"2026-06-09T01:05:48.084913Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.08715","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-09T01:05:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3REi7C4M+05UH6Gt7w0Q+ZMOr1Es8D1auc8daB99vfH6mjHSfZIoNtfEFVUwg2uAoT2hoWRlawJI5Tqd5cxXAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T10:44:27.774845Z"},"content_sha256":"951db9a3253ac23c45df778e66e3c889ff39e0905c7d5dff88c37a70c48fb694","schema_version":"1.0","event_id":"sha256:951db9a3253ac23c45df778e66e3c889ff39e0905c7d5dff88c37a70c48fb694"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:XJYGTX6ITVPAFITEQUSD3G2CLZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Operationalizing Linguistic Methods through Prompt-Engineering Skills: An Automatic Chinese Web Neologism Detection Pipeline","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Meichun Liu, Yufeng Wu","submitted_at":"2026-06-07T16:13:06Z","abstract_excerpt":"We present a method for automatic Chinese web neologism detection that operationalizes traditional linguistic identification principles as prompt-engineering skills. The method has four stages: tokenizer-independent character n-gram candidate generation; dictionary anchoring with a Pointwise Mutual Information pre-filter; a well-formedness skill based on Chinese word-formation principles; and a combined rule and three-way classification skill that distinguishes neologism, entity, and none. Applied to the BAAI CCI 3.0 corpus (267M documents), the method produces 226,959 classified candidates in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.08715","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.08715/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-09T01:05:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"62skFvGoGDyAt+ruDu7QRWrlB496+bwv/NG0D+JpwF4mJcuUgjfVDB2FQj514nAgwUJRXkFwEnjRPfOVzpzOBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T10:44:27.775220Z"},"content_sha256":"06eea6db80adda375f17c5da4aff8e67ed703cbb49d500fdff77704448ccd630","schema_version":"1.0","event_id":"sha256:06eea6db80adda375f17c5da4aff8e67ed703cbb49d500fdff77704448ccd630"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XJYGTX6ITVPAFITEQUSD3G2CLZ/bundle.json","state_url":"https://pith.science/pith/XJYGTX6ITVPAFITEQUSD3G2CLZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XJYGTX6ITVPAFITEQUSD3G2CLZ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T10:44:27Z","links":{"resolver":"https://pith.science/pith/XJYGTX6ITVPAFITEQUSD3G2CLZ","bundle":"https://pith.science/pith/XJYGTX6ITVPAFITEQUSD3G2CLZ/bundle.json","state":"https://pith.science/pith/XJYGTX6ITVPAFITEQUSD3G2CLZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XJYGTX6ITVPAFITEQUSD3G2CLZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:XJYGTX6ITVPAFITEQUSD3G2CLZ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"9f3f8a2e4bebdd7ee7dff5852a628d8a6628e69012dabea0800727ce46f1753c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-07T16:13:06Z","title_canon_sha256":"4ce3fbd3035c13a011036c8fd7a1d9bba917aa0ec816c6725dfab448ef77b4a2"},"schema_version":"1.0","source":{"id":"2606.08715","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.08715","created_at":"2026-06-09T01:05:48Z"},{"alias_kind":"arxiv_version","alias_value":"2606.08715v1","created_at":"2026-06-09T01:05:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.08715","created_at":"2026-06-09T01:05:48Z"},{"alias_kind":"pith_short_12","alias_value":"XJYGTX6ITVPA","created_at":"2026-06-09T01:05:48Z"},{"alias_kind":"pith_short_16","alias_value":"XJYGTX6ITVPAFITE","created_at":"2026-06-09T01:05:48Z"},{"alias_kind":"pith_short_8","alias_value":"XJYGTX6I","created_at":"2026-06-09T01:05:48Z"}],"graph_snapshots":[{"event_id":"sha256:06eea6db80adda375f17c5da4aff8e67ed703cbb49d500fdff77704448ccd630","target":"graph","created_at":"2026-06-09T01:05:48Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2606.08715/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present a method for automatic Chinese web neologism detection that operationalizes traditional linguistic identification principles as prompt-engineering skills. The method has four stages: tokenizer-independent character n-gram candidate generation; dictionary anchoring with a Pointwise Mutual Information pre-filter; a well-formedness skill based on Chinese word-formation principles; and a combined rule and three-way classification skill that distinguishes neologism, entity, and none. Applied to the BAAI CCI 3.0 corpus (267M documents), the method produces 226,959 classified candidates in","authors_text":"Meichun Liu, Yufeng Wu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-07T16:13:06Z","title":"Operationalizing Linguistic Methods through Prompt-Engineering Skills: An Automatic Chinese Web Neologism Detection Pipeline"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.08715","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:951db9a3253ac23c45df778e66e3c889ff39e0905c7d5dff88c37a70c48fb694","target":"record","created_at":"2026-06-09T01:05:48Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"9f3f8a2e4bebdd7ee7dff5852a628d8a6628e69012dabea0800727ce46f1753c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-07T16:13:06Z","title_canon_sha256":"4ce3fbd3035c13a011036c8fd7a1d9bba917aa0ec816c6725dfab448ef77b4a2"},"schema_version":"1.0","source":{"id":"2606.08715","kind":"arxiv","version":1}},"canonical_sha256":"ba7069dfc89d5e02a26485243d9b425e75f412a767189bbb4179af26bc4c48e1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ba7069dfc89d5e02a26485243d9b425e75f412a767189bbb4179af26bc4c48e1","first_computed_at":"2026-06-09T01:05:48.084913Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-09T01:05:48.084913Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gyjhyVLnBwWcYJdh+0/d0iJl6VPnQlm0b7UT4PbX9xxEPRXmTF5vt1l/EAggaCgUPD/55bVsrIZZwDdx9O6iDQ==","signature_status":"signed_v1","signed_at":"2026-06-09T01:05:48.085306Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.08715","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:951db9a3253ac23c45df778e66e3c889ff39e0905c7d5dff88c37a70c48fb694","sha256:06eea6db80adda375f17c5da4aff8e67ed703cbb49d500fdff77704448ccd630"],"state_sha256":"29826a0e28c8edeb5bd9a429de75718458644d08b4012d279b627cff2c8f7a0d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"78WrzMvWADZ07VDUgHsNZUQcAlxt102eq+5DTS6N0RaQxWEM6/YpUNrdwf82MagwmyQOih/bbTwRDohm0sBMBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T10:44:27.777154Z","bundle_sha256":"d7f7798ebcdd866994d0f89ab732f695a0b63358049af9aea0e781bfe38c758c"}}