{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:LW25T4TX57ZP33XAY2IBHPSUAN","short_pith_number":"pith:LW25T4TX","canonical_record":{"source":{"id":"2305.16426","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-05-25T18:56:26Z","cross_cats_sorted":[],"title_canon_sha256":"ed55bfef9052ade2705e5eb77c21452e8b6c2102595d0ef0a6a111c157d59ff8","abstract_canon_sha256":"73be57025f94d82820093ebf93a88b106bb443172460b839826ef0f89962709c"},"schema_version":"1.0"},"canonical_sha256":"5db5d9f277eff2fdeee0c69013be5403754f9201fba2528356f3a7b2e6114704","source":{"kind":"arxiv","id":"2305.16426","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.16426","created_at":"2026-07-05T07:03:26Z"},{"alias_kind":"arxiv_version","alias_value":"2305.16426v2","created_at":"2026-07-05T07:03:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.16426","created_at":"2026-07-05T07:03:26Z"},{"alias_kind":"pith_short_12","alias_value":"LW25T4TX57ZP","created_at":"2026-07-05T07:03:26Z"},{"alias_kind":"pith_short_16","alias_value":"LW25T4TX57ZP33XA","created_at":"2026-07-05T07:03:26Z"},{"alias_kind":"pith_short_8","alias_value":"LW25T4TX","created_at":"2026-07-05T07:03:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:LW25T4TX57ZP33XAY2IBHPSUAN","target":"record","payload":{"canonical_record":{"source":{"id":"2305.16426","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-05-25T18:56:26Z","cross_cats_sorted":[],"title_canon_sha256":"ed55bfef9052ade2705e5eb77c21452e8b6c2102595d0ef0a6a111c157d59ff8","abstract_canon_sha256":"73be57025f94d82820093ebf93a88b106bb443172460b839826ef0f89962709c"},"schema_version":"1.0"},"canonical_sha256":"5db5d9f277eff2fdeee0c69013be5403754f9201fba2528356f3a7b2e6114704","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:03:26.178286Z","signature_b64":"iFl6OALMBaX0QDGbDWwtyz+FB3hjKWOKCZcIwkDtwCGFd4qjX+TGsg2by6yb51i6IuJMSLLEqQagtrnWqiKQDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5db5d9f277eff2fdeee0c69013be5403754f9201fba2528356f3a7b2e6114704","last_reissued_at":"2026-07-05T07:03:26.177806Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:03:26.177806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.16426","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:03:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e0i13jypzaP0/zOhQ4npaC9VAxnz1iawkgmVDpc0W9wqFwEhZXMWEdn6e4j8oQ5VgWxJuk/Utizu8VQ9T2c8BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:45:17.095103Z"},"content_sha256":"206c9139da6b21d0917bd1a1456dc989e660bc2ce551afba79f9c10a67c78565","schema_version":"1.0","event_id":"sha256:206c9139da6b21d0917bd1a1456dc989e660bc2ce551afba79f9c10a67c78565"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:LW25T4TX57ZP33XAY2IBHPSUAN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Not wacky vs. definitely wacky: A study of scalar adverbs in pretrained language models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Isabelle Lorge, Janet Pierrehumbert","submitted_at":"2023-05-25T18:56:26Z","abstract_excerpt":"Vector space models of word meaning all share the assumption that words occurring in similar contexts have similar meanings. In such models, words that are similar in their topical associations but differ in their logical force tend to emerge as semantically close, creating well-known challenges for NLP applications that involve logical reasoning. Modern pretrained language models, such as BERT, RoBERTa and GPT-3 hold the promise of performing better on logical tasks than classic static word embeddings. However, reports are mixed about their success. In the current paper, we advance this discu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.16426","kind":"arxiv","version":2},"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/2305.16426/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":"2026-07-05T07:03:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tiuIsw1KJWcH2sNBwyOYvpqMed9zvdjZdiU1TnujwpXlp06Xgt3AqhTRorvkWnY1awRRIW7cHbVKPKe16u0YAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:45:17.095776Z"},"content_sha256":"3fbcbcd9cae3a5a1d8e77a59c01996ab148e8c4eb03accd7d51994f24fbd2c56","schema_version":"1.0","event_id":"sha256:3fbcbcd9cae3a5a1d8e77a59c01996ab148e8c4eb03accd7d51994f24fbd2c56"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LW25T4TX57ZP33XAY2IBHPSUAN/bundle.json","state_url":"https://pith.science/pith/LW25T4TX57ZP33XAY2IBHPSUAN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LW25T4TX57ZP33XAY2IBHPSUAN/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":"2026-07-05T15:45:17Z","links":{"resolver":"https://pith.science/pith/LW25T4TX57ZP33XAY2IBHPSUAN","bundle":"https://pith.science/pith/LW25T4TX57ZP33XAY2IBHPSUAN/bundle.json","state":"https://pith.science/pith/LW25T4TX57ZP33XAY2IBHPSUAN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LW25T4TX57ZP33XAY2IBHPSUAN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:LW25T4TX57ZP33XAY2IBHPSUAN","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":"73be57025f94d82820093ebf93a88b106bb443172460b839826ef0f89962709c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-05-25T18:56:26Z","title_canon_sha256":"ed55bfef9052ade2705e5eb77c21452e8b6c2102595d0ef0a6a111c157d59ff8"},"schema_version":"1.0","source":{"id":"2305.16426","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.16426","created_at":"2026-07-05T07:03:26Z"},{"alias_kind":"arxiv_version","alias_value":"2305.16426v2","created_at":"2026-07-05T07:03:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.16426","created_at":"2026-07-05T07:03:26Z"},{"alias_kind":"pith_short_12","alias_value":"LW25T4TX57ZP","created_at":"2026-07-05T07:03:26Z"},{"alias_kind":"pith_short_16","alias_value":"LW25T4TX57ZP33XA","created_at":"2026-07-05T07:03:26Z"},{"alias_kind":"pith_short_8","alias_value":"LW25T4TX","created_at":"2026-07-05T07:03:26Z"}],"graph_snapshots":[{"event_id":"sha256:3fbcbcd9cae3a5a1d8e77a59c01996ab148e8c4eb03accd7d51994f24fbd2c56","target":"graph","created_at":"2026-07-05T07:03:26Z","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/2305.16426/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vector space models of word meaning all share the assumption that words occurring in similar contexts have similar meanings. In such models, words that are similar in their topical associations but differ in their logical force tend to emerge as semantically close, creating well-known challenges for NLP applications that involve logical reasoning. Modern pretrained language models, such as BERT, RoBERTa and GPT-3 hold the promise of performing better on logical tasks than classic static word embeddings. However, reports are mixed about their success. In the current paper, we advance this discu","authors_text":"Isabelle Lorge, Janet Pierrehumbert","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-05-25T18:56:26Z","title":"Not wacky vs. definitely wacky: A study of scalar adverbs in pretrained language models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.16426","kind":"arxiv","version":2},"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":"sha256:206c9139da6b21d0917bd1a1456dc989e660bc2ce551afba79f9c10a67c78565","target":"record","created_at":"2026-07-05T07:03:26Z","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":"73be57025f94d82820093ebf93a88b106bb443172460b839826ef0f89962709c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-05-25T18:56:26Z","title_canon_sha256":"ed55bfef9052ade2705e5eb77c21452e8b6c2102595d0ef0a6a111c157d59ff8"},"schema_version":"1.0","source":{"id":"2305.16426","kind":"arxiv","version":2}},"canonical_sha256":"5db5d9f277eff2fdeee0c69013be5403754f9201fba2528356f3a7b2e6114704","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5db5d9f277eff2fdeee0c69013be5403754f9201fba2528356f3a7b2e6114704","first_computed_at":"2026-07-05T07:03:26.177806Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:03:26.177806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iFl6OALMBaX0QDGbDWwtyz+FB3hjKWOKCZcIwkDtwCGFd4qjX+TGsg2by6yb51i6IuJMSLLEqQagtrnWqiKQDw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:03:26.178286Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.16426","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:206c9139da6b21d0917bd1a1456dc989e660bc2ce551afba79f9c10a67c78565","sha256:3fbcbcd9cae3a5a1d8e77a59c01996ab148e8c4eb03accd7d51994f24fbd2c56"],"state_sha256":"fb1058ae12a82850b483de1b5b0a623a375967ed9f1d19f8e9eefc491067834e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ahJ5eVTGjMDbpmM5RhF7AdOz6N5sqF0xbPydEVcvmmsMNAhin9XN3Wro/uWLu1KnOXwhH7Ck0Kz5SuBpvU+DDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T15:45:17.099181Z","bundle_sha256":"88405e965fc5ee7c420f34038fb48dc1c41e5e3bbeb025daf58bccb727e87a33"}}